EMBEDDED SYSTEM PROJECTS - ABSTRACTS
The teleoperation of mobile social robots requires operators to understand facial gestures and other nonverbal communication from a person interacting with the robot. It is also critical for the operator to comprehend the surrounding environment in order to facilitate both navigation and human-robot interaction.
Allowing the operator to control the robot's gaze direction can help the operator observe a person's nonverbal communication; however, manually actuating a gaze increases the operator's workload and conflicts with the use of the robot's camera for navigation.
To address these problems, the authors developed a teleoperation system that combines automatic control of the robot's gaze and a 3-D graphical representation of the surrounding environment, such as location of items and configuration of a shop.
A study where a robot plays the role of a shopkeeper was conducted to validate the effectiveness of the proposed gaze-control technique and control interface. It was demonstrated that the combination of automatic gaze control and representations of spatial relationships improved the quality of the robot's interaction with the customer.
Allowing the operator to control the robot's gaze direction can help the operator observe a person's nonverbal communication; however, manually actuating a gaze increases the operator's workload and conflicts with the use of the robot's camera for navigation.
To address these problems, the authors developed a teleoperation system that combines automatic control of the robot's gaze and a 3-D graphical representation of the surrounding environment, such as location of items and configuration of a shop.
A study where a robot plays the role of a shopkeeper was conducted to validate the effectiveness of the proposed gaze-control technique and control interface. It was demonstrated that the combination of automatic gaze control and representations of spatial relationships improved the quality of the robot's interaction with the customer.
A Voice-Input Voice-Output Communication Aid for People With Severe Speech Impairment
A new form of augmentative and alternative communication (AAC) device for people with severe speech impairment—the voice-input voice-output communication aid(VIVOCA)—is described.
The VIVOCA recognizes the disordered speech of the user and builds messages, which are converted into synthetic speech. System development was carried out employing user-centered design and development methods, which identified and refined key requirements for the device. A novel methodology for building small vocabulary, speaker-dependent automatic speech recognizers with reduced amounts of training data, was applied.
Experiments showed that this method is successful in generating good recognition performance (mean accuracy 96%) on highly disordered speech, even when recognition perplexity is increased. The selected message-building technique traded off various factors including speed of message construction and range of available message outputs.
The VIVOCA was evaluated in a field trial by individuals with moderate to severe dysarthria and confirmed that they can make use of the device to produce intelligible speech output from disordered speech input. The trial highlighted some issues which limit the performance and usability of the device when applied in real usage situations, with mean recognition accuracy of 67% in these circumstances. These limitations will be addressed in future work.
The VIVOCA recognizes the disordered speech of the user and builds messages, which are converted into synthetic speech. System development was carried out employing user-centered design and development methods, which identified and refined key requirements for the device. A novel methodology for building small vocabulary, speaker-dependent automatic speech recognizers with reduced amounts of training data, was applied.
Experiments showed that this method is successful in generating good recognition performance (mean accuracy 96%) on highly disordered speech, even when recognition perplexity is increased. The selected message-building technique traded off various factors including speed of message construction and range of available message outputs.
The VIVOCA was evaluated in a field trial by individuals with moderate to severe dysarthria and confirmed that they can make use of the device to produce intelligible speech output from disordered speech input. The trial highlighted some issues which limit the performance and usability of the device when applied in real usage situations, with mean recognition accuracy of 67% in these circumstances. These limitations will be addressed in future work.
Automatic Control of Aircraft in Longitudinal Plane During Landing
Automatic control of aircraft during landing is discussed and a new structure of automatic landing system (ALS) is designed using the dynamic inversion concept and proportional-integral-derivative (PID) controllers in conventional and fuzzy variants. Theoretical results are validated by numerical simulations in the absence or presence of wind shears and sensor errors.
Autonomous Solar Powered Irrigation System
This paper gives information related to OFF grid application system, which is independent of supply from the grid. The source to generate electricity through renewable resources, we prefer sunlight as the main source.
The objective is to supply water for the fields through solar powered water pump and automate the system for better management of resources. The farmer (user) can water the fields from any place using GSM technique which provides an acknowledgement message about the situation.
The main advantage of this project is optimizing the power usage through water resource management and also saving government’s free subsidiary electricity. This proves an efficient and economy way of irrigation and this will automate the agriculture sector.
The objective is to supply water for the fields through solar powered water pump and automate the system for better management of resources. The farmer (user) can water the fields from any place using GSM technique which provides an acknowledgement message about the situation.
The main advantage of this project is optimizing the power usage through water resource management and also saving government’s free subsidiary electricity. This proves an efficient and economy way of irrigation and this will automate the agriculture sector.
A Smart Prepaid energy Metering system to control electricity theft
Power utilities in different countries especially in the developing ones are incurring huge losses due to electricity theft. This paper proposes a prepaid energy metering system to control electricity theft.
In this system a smart energy meter is installed in every consumer unit and a server is maintained at the service provider side. Both the meter and the server are equipped with GSM module which facilitates bidirectional communication between the two ends using the existing GSM infrastructure. Consumers can easily recharge their energy meter by sending a PIN number hidden in a scratch card to the server using SMS. This paper presents some measures to control meter bypassing and tampering.
The bidirectional GSM communication using SMS ensures the effectiveness of these measures. Pilferage of electricity can be substantially reduced by incorporating the proposed measures along with the prepaid metering scheme. Legal actions against dishonest consumers can also be taken in this system.
In this system a smart energy meter is installed in every consumer unit and a server is maintained at the service provider side. Both the meter and the server are equipped with GSM module which facilitates bidirectional communication between the two ends using the existing GSM infrastructure. Consumers can easily recharge their energy meter by sending a PIN number hidden in a scratch card to the server using SMS. This paper presents some measures to control meter bypassing and tampering.
The bidirectional GSM communication using SMS ensures the effectiveness of these measures. Pilferage of electricity can be substantially reduced by incorporating the proposed measures along with the prepaid metering scheme. Legal actions against dishonest consumers can also be taken in this system.
RFID-based digital content copy protection system in movie and audio rental agency
As media rental markets have expanded, a secure digital content protection system is urgently demanded. It is true that digital right management (DRM) has made tremendous progress in fighting piracy, but the pirated contents are still rampant due to the weakness of DRM systems. Because they are incapable of controlling external pirate action like analog/digital bus tampering.
In this paper, we propose a novel approach using RFID (Radio Frequency Identification) technology and cryptography algorithm to provide end-to-end protection.
In this paper, we propose a novel approach using RFID (Radio Frequency Identification) technology and cryptography algorithm to provide end-to-end protection.
Self-Powered Wireless Sensor for Air Temperature and Velocity Measurements With Energy Harvesting Capability
Air temperature and velocity measurements are important parameters in many applications. A self-powered sensor placed in a duct and powered by an electromechanical generator scavenging energy from the airflow has been designed and tested. It periodically transmits the measured air temperature and velocity to a receiving unit.
The system basically consists of two macroblocks, respectively: the self-power wireless sensor and the receiving unit. The self-powered sensor has a section devoted to the energy harvesting, exploiting the movement of an airscrew shaft keyed to a dc motor. The self-powered sensor adopts integrated devices in low-power technology, including a microcontroller, an integrated temperature sensor, and a radio-frequency transmitter at 433 MHz.
The system basically consists of two macroblocks, respectively: the self-power wireless sensor and the receiving unit. The self-powered sensor has a section devoted to the energy harvesting, exploiting the movement of an airscrew shaft keyed to a dc motor. The self-powered sensor adopts integrated devices in low-power technology, including a microcontroller, an integrated temperature sensor, and a radio-frequency transmitter at 433 MHz.
The data transmission is realized in Manchester encoding, with amplitude-shift-keying modulation at 433 MHz, allowing covering a distance between the sensor and the reader on the order of 4-5 m, depending on the power supplied in transmission. The air velocity is measured through the rotor frequency of the electromechanical generator, whereas, for the temperature, a commercial low-power sensor is used.
An experimental system has been designed and fabricated, demonstrating that the airflow harvester can power the self-powered wireless sensor permitting air temperature and velocity measurements. The system can be used for real-time monitoring of temperature and velocity. The sensor module placed into the duct does not require any batteries.
An experimental system has been designed and fabricated, demonstrating that the airflow harvester can power the self-powered wireless sensor permitting air temperature and velocity measurements. The system can be used for real-time monitoring of temperature and velocity. The sensor module placed into the duct does not require any batteries.
5.2-GHz RF Power Harvester in 0.18-m CMOS for Implantable Intraocular Pressure Monitoring
A first fully integrated 5.2-GHz CMOS-based RFpower harvester with an on-chip antenna is presented in this paper. The design is optimized for sensors implanted inside the eye to wirelessly monitor the intraocular press ure of glaucoma patients. It includes a five-stage RF rectifier with an on-chip antenna, a dc voltage limiter, two voltage sensors, a low dropout voltage regulator, and MOSCAP based on-chip storage.
The chip has been designed and fabricated in a standard 0.18-mCMOS technology. To emulate the eye environment in measurements, a custom test setup is developed that comprises Plexiglass cavities filled with saline solution. Measurements in this setup show that the proposed chip can be charged to 1 V wirelessly from a 5-W transmitter 3 cm away from the harvester chip.
The energy that is stored on the 5-nF on-chip MOSCAP when charged to 1 V is 2.5 nJ, which is sufficient to drive an arbitrary 100-W load for 9 s at regulated 0.8 V. Simulated efficiency of the rectifier is 42% at 7 dBm of input power.
The energy that is stored on the 5-nF on-chip MOSCAP when charged to 1 V is 2.5 nJ, which is sufficient to drive an arbitrary 100-W load for 9 s at regulated 0.8 V. Simulated efficiency of the rectifier is 42% at 7 dBm of input power.
A Contest-Oriented Project for Learning Intelligent Mobile Robots
A contest-oriented project for undergraduate students to learn implementation skills and theories related to intelligent mobile robots is presented in this paper. The project,related to Micromouse, Robotrace (Robotrace is the title of Taiwanese and Japanese robot races), and line-maze contests was developed by the embedded control system research group of the Department of Electronic Engineering, Lunghwa University of Science and Technology, Taiwan.
It targets both those students who have to earn credits for a one-year special topics course and those who are just interested in making robots, and it is designed to motivate them to learn digital motion control, path planning,attitude correction, curvature detection and maze-solving algorithms.
The students begin by getting acquainted with the development environment of microcontrollers, the characteristics of different sensors, and servomotor control techniques. Having learned these basic skills, they acquire further specific advanced skills and proceed to design their own mobile robots to compete in contests.
The special topics course students' robots must pass examination by five teachers. Blogs and a wiki Web site for recording students' progress and experiences enhance the project's learning outcomes. Although not every student wins a prize in the contests, student feedback still shows that the contest-oriented project did motivate them to acquire the skills necessary to build and operate intelligent mobile robots.
The students begin by getting acquainted with the development environment of microcontrollers, the characteristics of different sensors, and servomotor control techniques. Having learned these basic skills, they acquire further specific advanced skills and proceed to design their own mobile robots to compete in contests.
The special topics course students' robots must pass examination by five teachers. Blogs and a wiki Web site for recording students' progress and experiences enhance the project's learning outcomes. Although not every student wins a prize in the contests, student feedback still shows that the contest-oriented project did motivate them to acquire the skills necessary to build and operate intelligent mobile robots.
A Fire Detection and Rescue Support Framework with Wireless Sensor Networks
Recently, wireless sensor network (WSN) technology has been widely used in various fields such as public safety applications since it provides a wide range of surveillance and monitoring applications with an inexpensive price. In this paper, we investigate the use of wireless sensor network technology for fire detection and rescue system.
We propose a framework, which can detect fires promptly and support rescue activities, using wireless sensor devices. Our framework consists of fire detection sensor network, information gathering layer, middleware, and escape support system. We have implemented a test-bed and evaluated the performance of fire detection via experiments.
We propose a framework, which can detect fires promptly and support rescue activities, using wireless sensor devices. Our framework consists of fire detection sensor network, information gathering layer, middleware, and escape support system. We have implemented a test-bed and evaluated the performance of fire detection via experiments.
A Green Solution for Intelligent Metropolitan Heating system with uSDCards
In this paper, we present the architecture, design, and simulation of an intelligent system for Temperature Monitoring used in metropolitan heating. The system consists of several TelosB-compatible motes, a Nokia uSDCard, and a smart phone.
We use TelosB Motes to collect temperature data, and to transport the data to the smart phone. The uSDCard, as the middle layer, connects the smart phone with the ZigBee compatible devices. The smart phone, as the terminal, processes data and manages the TelosB Motes.
We use the smart phone as the final terminal because it has a rich set of user interfaces and has access to various kinds of networks, allowing our system to be extended more easily and more user-friendly. In real scenes, our system can reduce the temperature reading fluctuation, and ultimately save the energy consumption for heating companies, providing a better living environment for indoor users.
We use the smart phone as the final terminal because it has a rich set of user interfaces and has access to various kinds of networks, allowing our system to be extended more easily and more user-friendly. In real scenes, our system can reduce the temperature reading fluctuation, and ultimately save the energy consumption for heating companies, providing a better living environment for indoor users.
A Microcontroller based mobile robotic platform for odor detection
Recent applications of mobile robotics in odor detection field have driven an increasing interest of scientist and engineers. Several applications have been reported in areas as water and air monitoring; gas leakage detection; explosives, drugs or people detection and demining tasks, among others.
Many robotic platforms (i.e. hardware and software) have been proposed to carry out an odor detection task however, in this field, this remains an open research. This research requires the development and evaluation of a robust moile robotic platform which supports an odor sensory unit, as well as some development tools like PC communication, data saving and the odor delivery system.
This work has been focused on this topic. A LabVIEW virtual instrument was developed to allow data acquisition from sensors as well as motor commands, via serial port. The platform was experimentally validated using two reactive Braitenberg inspired algorithms.
Many robotic platforms (i.e. hardware and software) have been proposed to carry out an odor detection task however, in this field, this remains an open research. This research requires the development and evaluation of a robust moile robotic platform which supports an odor sensory unit, as well as some development tools like PC communication, data saving and the odor delivery system.
This work has been focused on this topic. A LabVIEW virtual instrument was developed to allow data acquisition from sensors as well as motor commands, via serial port. The platform was experimentally validated using two reactive Braitenberg inspired algorithms.
A Scheme for the Application of Smart Message Language in a Wireless Meter Reading System
In order to solve the problems of the communication among various metering devices in the traditional wireless meter reading system, Smart Message Language (SML) which is the definition of the German national standard for Automatic Meter Reading System is introduced.
In this paper, the Wireless Meter Reading system is developed based on WI-FI, with the monitoring terminal of the hardware platform made up of Marvell 88W8686, the ARM7 processor and peripheral circuits, using µC/OS-II operating system and LwIP protocol. VC++ and MDB database is used to develop a management software. SML protocol is adopted to design the format of the data frame to create a unified data structure for data procurement.
This system archives the function of reading meter data from hardware, data processing and storage. The experiment result proves that this type of data structure improves the transmission efficiency and the performance of the system and is suitable for implementation in low-power embedded systems
This system archives the function of reading meter data from hardware, data processing and storage. The experiment result proves that this type of data structure improves the transmission efficiency and the performance of the system and is suitable for implementation in low-power embedded systems
A Survey on Security for Mobile Devices
Nowadays, mobile devices are an important part of our everyday lives since they enable us to access a large variety of ubiquitous services. In recent years, the availability of these ubiquitous and mobile services has significantly increased due to the different form of connectivity provided by mobile devices, such as GSM, GPRS, Bluetooth and Wi-Fi.
In the same trend, the number and typologies of vulnerabilities exploiting these services and communication channels have increased as well. Therefore, smartphones may now represent an ideal target for malware writers.
As the number of vulnerabilities and, hence, of attacks increase, there has been a corresponding rise of security solutions proposed by researchers. Due to the fact that this research field is immature and still unexplored in depth, with this paper we aim to provide a structured and comprehensive overview of the research on security solutions for mobile devices.
This paper surveys the state of the art on threats, vulnerabilities and security solutions over the period 2004-2011, by focusing on high-level attacks, such those to user applications. We group existing approaches aimed at protecting mobile devices against these classes of attacks into different categories, based upon the detection principles, architectures, collected data and operating systems, especially focusing on IDS-based models and tools. With this categorization we aim to provide an easy and concise view of the underlying model adopted by each approach.
This paper surveys the state of the art on threats, vulnerabilities and security solutions over the period 2004-2011, by focusing on high-level attacks, such those to user applications. We group existing approaches aimed at protecting mobile devices against these classes of attacks into different categories, based upon the detection principles, architectures, collected data and operating systems, especially focusing on IDS-based models and tools. With this categorization we aim to provide an easy and concise view of the underlying model adopted by each approach.
A wearable inertial-sensing-based body sensor network for shoulder range of motion assessment
This paper presents a wearable inertial-sensing-based body sensor network (BSN) composed of two inertial modules that are placed on human upper limb for real-time human motion capture applications.
Each inertial module consists of an ARM-based 32-bit microcontroller (MCU), a triaxial accelerometer, a triaxial gyroscope, and a triaxial magnetometer. To estimate shoulder range of motion (ROM), the accelerations, angular velocities, and magnetic signals are collected and processed by a quaternion-based complementary nonlinear filter for minimizing the cumulative errors caused by the intrinsic noise/drift of the inertial sensors.
The proposed BSN is a cost-effective tool and can be used anywhere without any external reference device for shoulder ROM. The sensor fusion algorithm can reduce orientation error effectively and thus can assess shoulder joint motions accurately.
A Wireless Sensor network for greenhouse climate control
Using a wireless sensor network, the authors developed an online microclimate monitoring and control system for greenhouses. They field-tested the system in a greenhouse in Punjab, India, evaluating its measurement capabilities and network performance in real time.
A Zigbee-based wireless wearable electronic nose using flexible printed sensor array
A wearable electronic nose (e-nose) has been developed by integrating a low cost chemical sensor array with a wireless communication for applications in healthcare. Its sensing unit was fabricated by a fully inkjet-printing technique, comprising eight different sensor elements manufactured by varying printing patterns and sensing materials. These sensors have shown response to a wide variety of complex odors.
A wearable e-nose prototype using Zigbee wireless technology was designed as a compact armband for monitoring the axillary odor released from human body. Preliminary results based on principal component analysis (PCA) could classify different odors released from the human body upon various activities.
A wearable e-nose prototype using Zigbee wireless technology was designed as a compact armband for monitoring the axillary odor released from human body. Preliminary results based on principal component analysis (PCA) could classify different odors released from the human body upon various activities.
Advanced Electronic Stability Control (Esc) With Anti and Crash Location Sensing Using GSM
Vehicle Safety Systems Laboratory" integrated use of the CSIST in the national defense industry derivative technologies, the development of advanced safety vehicle (ASV; Advanced Safety Vehicle) related technologies, to enhance the civil technology industry efficiency and safety of passers-by, and the combination of vehicles optoelectronics industry-funded advantage of the next wave for the electronics industry to contribute to the development of key technologies.
An Active-Shunt Diverter for On-load Tap Changers
This paper presents a new hybrid diverter design for on-load tap changers. The design uses “active-shunt” current diversion principles. At its core, the design employs a low-voltage high-current switch-mode amplifier to divert current out of the mechanical contacts and into a pair of anti-parallel thyristors.
Commutation between transformer taps may then be performed by the thyristors. The amplifier and thyristors are placed outside the normal load current path and only conduct during a tap change, producing efficiency savings and improving robustness when compared to previous hybrid on-load tap changer implementations.
An amplifier control loop that autonomously produces zero-current conditions at switch opening and zero-voltage conditions at switch closure is demonstrated. Experimental results investigating the wear characteristics of contacts operated under the new hybrid diverter are presented, along with comparison results from a passive-type switching scheme. Contact lifetime of more than 25 million operations is demonstrated under the new scheme
An apparatus in monitoring the energy charging system
In this article the implementation of an uninterrupted solar energy surveillance system is compl. The completed system is comprised of three major sub-systems that include a charging sub-system, a control sub-system and a display sub-system. Based on several transmission standards, including Bluetooth, Wifi and Zigbee capability combined with wireless transmission techniques, the proposed surveillance system is designed for monitoring a solar energy system. The performance of the simulated WSSs is evaluated using statistical report results. The proposed surveillance system can be fully extended to several different kinds of applications, such as, health care and environmental inspection. The experimental measurement results significantly show that channel fading over the propagation channel dominates the developed system performance.
Analysis of an Indoor Biomedical Radar-Based System for Health Monitoring
Innovative technology approaches have been increasingly investigated for the last two decades aiming at human-being long-term monitoring. However, current solutions suffer from critical limitations.
In this paper, a complete system for contactless health-monitoring in home environment is presented. For the first time, radar, wireless communications, and data processing techniques are combined, enabling contactless fall detection and tagless localization.
Practical limitations are considered and properly dealt with. Experimental tests, conducted with human volunteers in a realistic room setting, demonstrate an adequate detection of the target's absolute distance and a success rate of 94.3% in distinguishing fall events from normal movements. The volunteers were free to move about the whole room with no constraints in their movements.
In this paper, a complete system for contactless health-monitoring in home environment is presented. For the first time, radar, wireless communications, and data processing techniques are combined, enabling contactless fall detection and tagless localization.
Practical limitations are considered and properly dealt with. Experimental tests, conducted with human volunteers in a realistic room setting, demonstrate an adequate detection of the target's absolute distance and a success rate of 94.3% in distinguishing fall events from normal movements. The volunteers were free to move about the whole room with no constraints in their movements.
Application of temperature compensated ultrasonic ranging for blind person and verification using MATLAB
This paper contains a method to implement a mobility aid for blind person and also can be used in automatic robots, self-propelling vehicles in automated production factories etc.
Model contains signal processing unit with PIC microcontroller which receives data from Ultrasonic sensor and Temperature sensor then processed it and delivers it to the computer using serial input/output port & gives alert to the blind person using voice processor with earphone.
Paper contains temperature compensation method to reduce the error in measurement of distance using ultrasonic sensors. Signal processing unit contains PIC microcontroller which is used for interfacing between different sensors and computer. Then received data is verified using MATLAB
Model contains signal processing unit with PIC microcontroller which receives data from Ultrasonic sensor and Temperature sensor then processed it and delivers it to the computer using serial input/output port & gives alert to the blind person using voice processor with earphone.
Paper contains temperature compensation method to reduce the error in measurement of distance using ultrasonic sensors. Signal processing unit contains PIC microcontroller which is used for interfacing between different sensors and computer. Then received data is verified using MATLAB
Artificial redirection of sensation from prosthetic fingers to the phantom hand map on transradial amputees vibrotactile versus mechanotactile sensory feedback
This work assesses the ability of transradial amputees to discriminate multi-site tactile stimuli in sensory discrimination tasks. It compares different sensory feedback modalities using an artificial hand prosthesis in: 1) a modality matched paradigm where pressure recorded on the five fingertips of the hand was fed back as pressure stimulation on five target points on the residual limb; and 2) a modality mismatched paradigm where the pressures were transformed into mechanical vibrations and fed back.
Eight transradial amputees took part in the study and were divided in two groups based on the integrity of their phantom map; group A had a complete phantom map on the residual limb whereas group B had an incomplete or nonexisting map.
The ability in localizing stimuli was compared with that of 10 healthy subjects using the vibration feedback and 11 healthy subjects using the pressure feedback (in a previous study), on their forearms, in similar experiments. Results demonstrate that pressure stimulation surpassed vibrotactile stimulation in multi-site sensory feedback discrimination.
Furthermore, we demonstrate that subjects with a detailed phantom map had the best discrimination performance and even surpassed healthy participants for both feedback paradigms whereas group B had the worst performance overall. Finally, we show that placement of feedback devices on a complete phantom map improves multi-site sensory feedback discrimination, independently of the feedback modality.
Eight transradial amputees took part in the study and were divided in two groups based on the integrity of their phantom map; group A had a complete phantom map on the residual limb whereas group B had an incomplete or nonexisting map.
The ability in localizing stimuli was compared with that of 10 healthy subjects using the vibration feedback and 11 healthy subjects using the pressure feedback (in a previous study), on their forearms, in similar experiments. Results demonstrate that pressure stimulation surpassed vibrotactile stimulation in multi-site sensory feedback discrimination.
Furthermore, we demonstrate that subjects with a detailed phantom map had the best discrimination performance and even surpassed healthy participants for both feedback paradigms whereas group B had the worst performance overall. Finally, we show that placement of feedback devices on a complete phantom map improves multi-site sensory feedback discrimination, independently of the feedback modality.
Automated Control System for Air Pollution Detection in Vehicles
Vehicles have become an integral part of every one's life. Situations and circumstances demand the usage of vehicles in this fast paced urban life. As a coin has two sides, this has its own effects, one of the main side effects being air pollution. Every vehicle will have emission but the problem occurs when it is beyond the standardized values.
The primary reason for this breach of emission level being the incomplete combustion of fuel supplied to engine, which is due to the improper maintenance of vehicles. This emission from vehicles cannot be completely avoided but, it definitely can be controlled. With the evolvement of semi-conductor sensors for detecting the various gases, this paper aims at using those semi-conductor sensors at the emission outlets of vehicles which detects the level of pollutants and also indicates this level with a meter.
When the pollution/ emission level shoots beyond the already set threshold level, there will be a buzz in the vehicle to indicate that the limit has been breached and the vehicle will stop after a certain period of time, a cushion time given for the driver to park his/her vehicle. During this time period, the GPS starts locating the nearest service stations.
After the timer runs out, the fuel supplied to the engine will be cut-off and the vehicle has to be towed to the mechanic or to the nearest service station. The synchronization and execution of the entire process is monitored and controlled by a micro controller. This paper, when augmented as a real time project, will benefit the society and help in reducing the air pollution.
The primary reason for this breach of emission level being the incomplete combustion of fuel supplied to engine, which is due to the improper maintenance of vehicles. This emission from vehicles cannot be completely avoided but, it definitely can be controlled. With the evolvement of semi-conductor sensors for detecting the various gases, this paper aims at using those semi-conductor sensors at the emission outlets of vehicles which detects the level of pollutants and also indicates this level with a meter.
When the pollution/ emission level shoots beyond the already set threshold level, there will be a buzz in the vehicle to indicate that the limit has been breached and the vehicle will stop after a certain period of time, a cushion time given for the driver to park his/her vehicle. During this time period, the GPS starts locating the nearest service stations.
After the timer runs out, the fuel supplied to the engine will be cut-off and the vehicle has to be towed to the mechanic or to the nearest service station. The synchronization and execution of the entire process is monitored and controlled by a micro controller. This paper, when augmented as a real time project, will benefit the society and help in reducing the air pollution.
Biomedical sensor network for cardiovascular fitness and activity monitoring
This paper describes a prototype model for cardiovascular activity and fitness monitoring system based on IEEE 11073 family of standard for medical device communication. It identifies basic requirements for developing a biomedical sensor network having resource limited sensor nodes to acquire, retrieve and communicate various physiological parameters while using short range wireless technologies.
IEEE 11073-10441 defines the set of protocols for tele-health environment at application layer and rest of the communication infrastructure is covered by the medical grade ZigBee network. In healthcare, space ZigBee provides an industry-wide standard for exchanging data between a variety of medical and non-medical devices and ZigBee enabled medical devices are fully compatible with ISO/IEEE 11073 for point-of-care medical device communication.
The proposed prototype model addresses design and development issues required to report any severe cardiovascular malfunctioning without compromising mobility and convenience of the patient.
IEEE 11073-10441 defines the set of protocols for tele-health environment at application layer and rest of the communication infrastructure is covered by the medical grade ZigBee network. In healthcare, space ZigBee provides an industry-wide standard for exchanging data between a variety of medical and non-medical devices and ZigBee enabled medical devices are fully compatible with ISO/IEEE 11073 for point-of-care medical device communication.
The proposed prototype model addresses design and development issues required to report any severe cardiovascular malfunctioning without compromising mobility and convenience of the patient.
Bounded Constrained Filtering for GPSINS Integration
This paper considers estimation problems where inequality constraints are imposed on the outputs of linear systems and can be modeled by nonlinear functions. In this case, censoring functions can be designed to constrain measurements for use by filters and smoothers.
It is established that the filter and smoother output estimates are unbiased, provided that the underlying probability density functions are even and the censoring functions are odd. The Bounded Real Lemma is employed to ensure that the output estimates satisfy a performance criterion.
A global positioning system (GPS) and inertial navigation system (INS) integration application is discussed in which a developed solution exhibits improved performance during GPS outages when a priori information is used to constrain the altitude and velocity measurements.
It is established that the filter and smoother output estimates are unbiased, provided that the underlying probability density functions are even and the censoring functions are odd. The Bounded Real Lemma is employed to ensure that the output estimates satisfy a performance criterion.
A global positioning system (GPS) and inertial navigation system (INS) integration application is discussed in which a developed solution exhibits improved performance during GPS outages when a priori information is used to constrain the altitude and velocity measurements.
Building point of care health technologies on the IEEE 11073 health device standards
We describe a complete point of care health system implemented using the IEEE 11073 health device standards and ZigBee health care profile and following the Continua Alliance guidelines. We exploit the interoperability and wide range of specializations to implement four physiological devices and three environmental sensors.
Within our projects, we have demonstrated the versatility of the Continua architecture by implementing the AHD within a smart meter, a wall socket plugin gateway and PC based application.
We are evaluating clinical impact of the integrated sensor platform to manage frail elderly and diabetes patients. Experience shows that the standards provide the advantage of a rapid development environment, and will offer an increasingly wide range of commercial devices as they are adopted.
Within our projects, we have demonstrated the versatility of the Continua architecture by implementing the AHD within a smart meter, a wall socket plugin gateway and PC based application.
We are evaluating clinical impact of the integrated sensor platform to manage frail elderly and diabetes patients. Experience shows that the standards provide the advantage of a rapid development environment, and will offer an increasingly wide range of commercial devices as they are adopted.
Capacitive seat sensors for multiple occupancy detection using a low-cost setup
The Minibus public transportation sector and road safety remains a significant challenge in Africa. We propose a low cost system to monitor the taxi industry and encourage safe driving. A low cost capacitive proximity sensor for seat occupancy detection based on the loading mode capacitive sensing technique is designed.
The capacitive sensor uses a single electrode to detect an occupant. We use ZigBee modules for a dynamic wireless system integration where sensors can be added or removed without modifications.
A mathematical model of the capacitive sensor is developed and we determine the capacitance on the sensor's electrode. The occupied capacitance is double the unoccupied capacitance. Our results show that the proposed capacitive sensor can distinguish clearly between an unoccupied and occupied seat.
The capacitive sensor uses a single electrode to detect an occupant. We use ZigBee modules for a dynamic wireless system integration where sensors can be added or removed without modifications.
A mathematical model of the capacitive sensor is developed and we determine the capacitance on the sensor's electrode. The occupied capacitance is double the unoccupied capacitance. Our results show that the proposed capacitive sensor can distinguish clearly between an unoccupied and occupied seat.
Child Activity Recognition Based on Cooperative Fusion Model of a Triaxial Accelerometer and a Barometric Pressure Sensor
This paper presents a child activity recognition approach using a single 3-axis accelerometer and a barometric pressure sensor worn on a waist of the body to prevent child accidents such as unintentional injuries at home. Labeled accelerometer data are collected from children of both sexes up to the age of 16 to 29 months.
To recognize daily activities, mean, standard deviation, and slope of time-domain features are calculated over sliding windows. In addition, the FFT analysis is adopted to extract frequency-domain features of the aggregated data, and then energy and correlation of acceleration data are calculated.
Child activities are classified into 11 daily activities which are wiggling, rolling, standing still, standing up, sitting down, walking, toddling, crawling, climbing up, climbing down, and stopping. The overall accuracy of activity recognition was 98.43% using only a single- wearable triaxial accelerometer sensor and a barometric pressure sensor with a support vector machine.
To recognize daily activities, mean, standard deviation, and slope of time-domain features are calculated over sliding windows. In addition, the FFT analysis is adopted to extract frequency-domain features of the aggregated data, and then energy and correlation of acceleration data are calculated.
Child activities are classified into 11 daily activities which are wiggling, rolling, standing still, standing up, sitting down, walking, toddling, crawling, climbing up, climbing down, and stopping. The overall accuracy of activity recognition was 98.43% using only a single- wearable triaxial accelerometer sensor and a barometric pressure sensor with a support vector machine.
Cooperative Wireless-Based Obstacle Object Mapping and See-Through Capabilities in Robotic Networks.
In this paper, we develop a theoretical and experimental framework for the mapping of obstacles (including occluded ones), in a robotic cooperative network, based on a small number of wireless channel measurements. This would allow the robots to map an area before entering it.
We consider three approaches based on coordinated space, random space, and frequency sampling, and show how the robots can exploit the sparse representation of the map in space, wavelet or spatial variations, in order to build it with minimal sensing.
We then show the underlying tradeoffs of all the possible sampling, sparsity and reconstruction techniques. Our simulation and experimental results show the feasibility and performance of the proposed framework.
More specifically, using our experimental robotic platform, we show preliminary results in successfully mapping a number of real obstacles and having see-through capabilities with real structures, despite the practical challenges presented by multipath fading.
We consider three approaches based on coordinated space, random space, and frequency sampling, and show how the robots can exploit the sparse representation of the map in space, wavelet or spatial variations, in order to build it with minimal sensing.
We then show the underlying tradeoffs of all the possible sampling, sparsity and reconstruction techniques. Our simulation and experimental results show the feasibility and performance of the proposed framework.
More specifically, using our experimental robotic platform, we show preliminary results in successfully mapping a number of real obstacles and having see-through capabilities with real structures, despite the practical challenges presented by multipath fading.
Coordinator Traffic Diffusion for Data-Intensive Zigbee Transmission in Real-time Electrocardiography Monitoring
Zigbee is expected to have an explosive growth in wireless medical monitoring systems because it possesses the advantages of low cost, safe power strength and easy deployment. However, little work focuses on solving the bottleneck issue at the Zigbee coordinator in a data-intensive system to guarantee transmission reliability of life-critical data.
This paper proposes Coordinator Traffic Diffusion (CTD) method to redirect excessive traffic from Coordinator to the Sink in Electrocardiography (ECG) medical application. CTD router, which implements CTD design, automatically redirects ECG data traffic to the sink node without involving the Coordinator, and thus reliable real-time ECG monitoring service can be delivered precisely. CTD design is tested in both TI CC2530 Zigbee platform and NS2 simulation.
Experiment result demonstrates CTD design can assist routers in successfully delivering real-time ECG data samples reliably with the best transmission rate, 24 Kbps. This performance cannot be achieved by the original Zigbee design.
This paper proposes Coordinator Traffic Diffusion (CTD) method to redirect excessive traffic from Coordinator to the Sink in Electrocardiography (ECG) medical application. CTD router, which implements CTD design, automatically redirects ECG data traffic to the sink node without involving the Coordinator, and thus reliable real-time ECG monitoring service can be delivered precisely. CTD design is tested in both TI CC2530 Zigbee platform and NS2 simulation.
Experiment result demonstrates CTD design can assist routers in successfully delivering real-time ECG data samples reliably with the best transmission rate, 24 Kbps. This performance cannot be achieved by the original Zigbee design.
Deep Sea Fishermen Patrol System for Coastal Intruder Positioning
This paper introduces a design which deals with an innovative handheld device which would transform the fisherman community as the eyes and ears of the Indian Coastguard. Upon sighting an intruder or poacher, the device allows fisherman to calculate its exact location using the integrated GPS receiver, and radiates the information to the nearest coastguard station via GSM communication.
The coastguard is then able to dispatch a patrol boat to intercept the intruder. The device would also warns the fisherman (beep and vibrate) when they approach near the national sea border and controls them to trawl (go fishing) within the correct region safely. Community surveillance allows the coastguard to patrol efficiently
The coastguard is then able to dispatch a patrol boat to intercept the intruder. The device would also warns the fisherman (beep and vibrate) when they approach near the national sea border and controls them to trawl (go fishing) within the correct region safely. Community surveillance allows the coastguard to patrol efficiently
Design and development of digital PID controller for DC motor drive system using embedded platform for mobile robot
In Agriculture industry, plants are prone to diseases caused by pathogens and environment conditions and it is a prime cause to lose of revenue. It requires continuous monitoring of plants and environment parameters to overcome this problem. A mobile Robotic system for monitoring these parameters using wireless network has been envisaged here and developed based on ARM-Linux platform.
Robotic platform consists of ARM9 based S3C2440 processor from SAMSUNG and Linux Kernel , Motor driver, robot mechanical assembly. The farm environment and plant condition such as temperature, humidity soil moisture content etc. are continuously monitored through suitable data acquisition system incorporated in the robotic system. A servo motor based robotic arm is designed for collecting soil sample and test various soil parameters.
A closed loop feedback algorithm based on Digital PID controller has been developed for precise position and speed control of mobile robot. The wireless control of mobile robot and monitored data acquisition is accomplished using zigbee wireless protocol. For displaying acquired data on host system a Graphical user interface is designed using qt creater framework.
For independent functioning of mobile robot, application program is written in c language and cross compiled using arm-linux-gcc compiler on Ubuntu 10.04 platform and ported on the memory of ARM processor.
Robotic platform consists of ARM9 based S3C2440 processor from SAMSUNG and Linux Kernel , Motor driver, robot mechanical assembly. The farm environment and plant condition such as temperature, humidity soil moisture content etc. are continuously monitored through suitable data acquisition system incorporated in the robotic system. A servo motor based robotic arm is designed for collecting soil sample and test various soil parameters.
A closed loop feedback algorithm based on Digital PID controller has been developed for precise position and speed control of mobile robot. The wireless control of mobile robot and monitored data acquisition is accomplished using zigbee wireless protocol. For displaying acquired data on host system a Graphical user interface is designed using qt creater framework.
For independent functioning of mobile robot, application program is written in c language and cross compiled using arm-linux-gcc compiler on Ubuntu 10.04 platform and ported on the memory of ARM processor.
Design and fabrication of a miniaturized ECG system with Bluetooth connectivity
The technological advancements in today's contemporary world has paved a way for miniaturization of devices. This has helped to provide proper and effective way of analyzing various body conditions and diseases.
The contraction and relaxation of the cardiac musclesresult in generationof electrical potential which could be used to diagnose various disorders of the heart. The aim of this project is to design a miniaturized ECG system which could help the physician to perform preliminary diagnosis of the heart. The proposed system has a microcontroller which has been programmed to indicate the working conditon of the heart based on the heart rate.
The system has an alarm circuit to indicate any abnormality present in the heart such as Bradycardia and Tachycardia. This system is built with a provision of enabling wireless transmission of ECG signals to a PC through Bluetooth.
This helps the doctor to have visual description of the subject ECG without the need of mounted monitors. The experimental results show that device is clinically approbated, compact,cost effective and easy to use.
The contraction and relaxation of the cardiac musclesresult in generationof electrical potential which could be used to diagnose various disorders of the heart. The aim of this project is to design a miniaturized ECG system which could help the physician to perform preliminary diagnosis of the heart. The proposed system has a microcontroller which has been programmed to indicate the working conditon of the heart based on the heart rate.
The system has an alarm circuit to indicate any abnormality present in the heart such as Bradycardia and Tachycardia. This system is built with a provision of enabling wireless transmission of ECG signals to a PC through Bluetooth.
This helps the doctor to have visual description of the subject ECG without the need of mounted monitors. The experimental results show that device is clinically approbated, compact,cost effective and easy to use.
Designing and Implementing a Human-Robot Team for Social Interactions
This study provides an in-depth analysis and practical solution to the problem of designing and implementing a human-robot team for simple conversational interactions.
Models for operation timing, customer satisfaction and customer-robot interaction are presented, based on which a simulation tool is developed to estimate fan-out and robot team performance. Techniques for managing interaction flow and operator task assignment are introduced.
In simulation, the effectiveness of different techniques and factors related to team performance are studied. A case study on deploying multiple robots in a shopping mall is then presented to demonstrate the usefulness of our study in helping the design and implementation of social robots in real-world settings
Models for operation timing, customer satisfaction and customer-robot interaction are presented, based on which a simulation tool is developed to estimate fan-out and robot team performance. Techniques for managing interaction flow and operator task assignment are introduced.
In simulation, the effectiveness of different techniques and factors related to team performance are studied. A case study on deploying multiple robots in a shopping mall is then presented to demonstrate the usefulness of our study in helping the design and implementation of social robots in real-world settings
Development of a ZigBee-Based Wireless Sensor Network System
With ZigBee technology, wireless sensor networks are being widely deployed. In this paper, we develop a ZigBee-based wireless sensor network system based on CC2530 system-on-chip of Texas Instruments (TI). Temperature acquisition is implemented for verification of the system.
Embedded Power and Energy Measurement System Based on an Analog Multiplier
This paper deals with the development of an analog electronic wattmeter based on a high-accuracy electronic four-quadrant multiplier and appropriate amplifying and averaging circuits.
The proposed instrument presents a simple design and is constructed using commercially available components. Its main advantage is that it can be integrated with the signal conditioning circuit, obtaining low cost, high resolution, and reduced dimensions. It can measure in circuits with very low power factors and nonsinusoidal waveforms.
The implemented prototype is a portable laboratory instrument, integrated with a digital system capable of processing the signals, and displaying the main parameters of both electric power and energy. It has been designed to easily integrate the main blocks in that either industrial or civil equipment requiring the power measurement for monitoring or control purposes.
A Fluke 6100 A power standard is used to calibrate the wattmeter over a wide range of current magnitudes and widths and at power factors down to 0.02; several results are reported and discussed.
The proposed instrument presents a simple design and is constructed using commercially available components. Its main advantage is that it can be integrated with the signal conditioning circuit, obtaining low cost, high resolution, and reduced dimensions. It can measure in circuits with very low power factors and nonsinusoidal waveforms.
The implemented prototype is a portable laboratory instrument, integrated with a digital system capable of processing the signals, and displaying the main parameters of both electric power and energy. It has been designed to easily integrate the main blocks in that either industrial or civil equipment requiring the power measurement for monitoring or control purposes.
A Fluke 6100 A power standard is used to calibrate the wattmeter over a wide range of current magnitudes and widths and at power factors down to 0.02; several results are reported and discussed.
Embedded temperature monitoring system with a microcontroller used in the automotive industry
This paper presents an embedded temperature acquisition system. The temperature acquisition is made with a temperature sensor and a microcontroller. The temperature sensor is an analogical sensor, this way for the acquisition the microcontroller's ADC was used. If the formula is changed than the program can be generalized for any temperature sensor.
Engineering Challenges for Instrumenting and Controlling Integrated Organ-on-Chip Systems
The sophistication and success of recently reported microfabricated organs-on-chips and human organ constructs have made it possible to design scaled and interconnected organ systems that may significantly augment the current drug development pipeline and lead to advances in systems biology.
Physiologically realistic live microHuman (µHu) and milliHuman (mHu) systems operating for weeks to months present exciting and important engineering challenges such as determining the appropriate size for each organ to ensure appropriate relative organ functional activity, achieving appropriate cell density, providing the requisite universal perfusion media, sensing the breadth of physiological responses, and maintaining stable control of the entire system, while maintaining fluid scaling that consists of ~5 mL for the mHu and ~5 µL for the µHu.
We believe that successful mHu and µHu systems for drug development and systems biology will require low-volume microdevices that support chemical signaling, microfabricated pumps, valves and microformulators, automated optical microscopy, electrochemical sensors for rapid metabolic assessment, ion mobility-mass spectrometry for real-time molecular analysis, advanced bioinformatics, and machine learning algorithms for automated model inference and integrated electronic control. Toward this goal, we are building functional prototype components and are working toward top-down system integration.
Physiologically realistic live microHuman (µHu) and milliHuman (mHu) systems operating for weeks to months present exciting and important engineering challenges such as determining the appropriate size for each organ to ensure appropriate relative organ functional activity, achieving appropriate cell density, providing the requisite universal perfusion media, sensing the breadth of physiological responses, and maintaining stable control of the entire system, while maintaining fluid scaling that consists of ~5 mL for the mHu and ~5 µL for the µHu.
We believe that successful mHu and µHu systems for drug development and systems biology will require low-volume microdevices that support chemical signaling, microfabricated pumps, valves and microformulators, automated optical microscopy, electrochemical sensors for rapid metabolic assessment, ion mobility-mass spectrometry for real-time molecular analysis, advanced bioinformatics, and machine learning algorithms for automated model inference and integrated electronic control. Toward this goal, we are building functional prototype components and are working toward top-down system integration.
Environment monitoring and device control using ARM based embedded controlled sensor network
Embedded controlled sensor network is the technology used to implement environmental solutions effectively. Many researchers have been making attempts to develop the embedded controlled sensor network. The existing systems are bulky, very costly and difficult to maintain. The proposed system is cost effective and controlled by user friendly embedded systems. In the proposed system ARM based microcontroller and wireless sensors are used to control the various devices and to monitor the information regarding the environment using Zigbee and GSM technologies.
HandiCom - Handheld Deaf and Dumb Communication Device based on Gesture to Voice and Speech to Image Word Translation with SMS Sending and Language
Our project aim is to build a handheld device that would help deaf and dumb people to communicate with others in every day spoken language such as English. Deaf and dumb often communicate via sign language, a kind of representation of words through hand and finger positions. But it has got serious limitations because it is not easy to understand by a normal listener on the opposite and to make things worse, not many in the world know sign language at all.
Also, it is difficult to represent all the words of a plain language like English into a sign language symbol. Even if there is one, then learning and using them would be tough and cumbersome.
In this paper, we will focus on the history of communication technolgy that have given better access to the world for those with sensory disabilities. The areas that will be covered are communication technologies that improve or augment hearing and vision, and technologies that support alternatives strategies to communication without hearing and /or vision
Also, it is difficult to represent all the words of a plain language like English into a sign language symbol. Even if there is one, then learning and using them would be tough and cumbersome.
In this paper, we will focus on the history of communication technolgy that have given better access to the world for those with sensory disabilities. The areas that will be covered are communication technologies that improve or augment hearing and vision, and technologies that support alternatives strategies to communication without hearing and /or vision
Hardware Demonstration of a Home Energy Management System for Demand Response Applications
A Home Energy Management (HEM) system plays a crucial role in realizing residential Demand Response (DR) programs in the smart grid environment. It provides a homeowner the ability to automatically perform smart load controls based on utility signals, customer's preference and load priority.
This paper presents the hardware demonstration of the proposed HEM system for managing end-use appliances. The HEM's communication time delay to perform load control is analyzed, along with its residual energy consumption.
This paper presents the hardware demonstration of the proposed HEM system for managing end-use appliances. The HEM's communication time delay to perform load control is analyzed, along with its residual energy consumption.
Implementation of Automatic Gas Monitoring in a Domestic Energy Management System
A domestic energy management system provides effective positive behaviour change by offering end users direct and ambient feedback based on their monitored energy consumption and experiences. DEHEMS, as a wide scale domestic energy monitoring and managing system differs from others by enabling real-time and historical electricity monitoring and feedback.
However, there is also a requirement to be able to monitor and report domestic gas consumption in order to reason and represent more complete energy feedback information to achieve effect positive behaviour changes.
In this paper, we present the gas monitoring system in DEHEMS, that implements automatic retrieval of gas readings. We describe how the system is designed, integrated within the DEHEMS architecture, as well as its implementation and deployment.
However, there is also a requirement to be able to monitor and report domestic gas consumption in order to reason and represent more complete energy feedback information to achieve effect positive behaviour changes.
In this paper, we present the gas monitoring system in DEHEMS, that implements automatic retrieval of gas readings. We describe how the system is designed, integrated within the DEHEMS architecture, as well as its implementation and deployment.
Integrated design of efficient & reliable motor drive and PFC using low cost microcontroller with embedded PGAs and CLA
Heating ventilation and air conditioning (HVAC) drives commonly utilize variable speed control to maximize efficiency and increasingly power factor correction (PFC) stage in the rectifier design to comply with regulations, such as IEC 61000-3-2, which limit the input current harmonics. Cycle by cycle control is desired for both the PFC stage and motor inverter.
Closed loop control of these stages consumes the entire bandwidth available on a typical microcontroller leaving no bandwidth to implement fault diagnostics, housekeeping and host functions.
This paper presents design of motor control and PFC using a single low cost microcontroller (MCU- TI TMS320F2805x) with embedded analog subsystem consisting of programmable gate arrays (PGA) to sense the shunt inverter currents, windowed comparators and DACs for programmable protection levels; and small footprint control law accelerator (CLA) to double the bandwidth.
The integrated design reduces the number of components, reducing board size and build cost and enables on the fly changes which brings enhanced control possibilities for a cost sensitive market without compromising on cost.
Closed loop control of these stages consumes the entire bandwidth available on a typical microcontroller leaving no bandwidth to implement fault diagnostics, housekeeping and host functions.
This paper presents design of motor control and PFC using a single low cost microcontroller (MCU- TI TMS320F2805x) with embedded analog subsystem consisting of programmable gate arrays (PGA) to sense the shunt inverter currents, windowed comparators and DACs for programmable protection levels; and small footprint control law accelerator (CLA) to double the bandwidth.
The integrated design reduces the number of components, reducing board size and build cost and enables on the fly changes which brings enhanced control possibilities for a cost sensitive market without compromising on cost.
Integrated Lane and Vehicle Detection, Localization, and Tracking A Synergistic Approach
In this paper, we introduce a synergistic approach to integrated lane and vehicle tracking for driver assistance. The approach presented in this paper results in a final system that improves on the performance of both lane tracking and vehicle tracking modules.
Further, the presented approach introduces a novel approach to localizing and tracking other vehicles on the road with respect to lane position, which provides information on higher contextual relevance that neither the lane tracker nor vehicle tracker can provide by itself.
Improvements in lane tracking and vehicle tracking have been extensively quantified. Integrated system performance has been validated on real-world highway data. Without specific hardware and software optimizations, the fully implemented system runs at near-real-time speeds of 11 frames per second.
Further, the presented approach introduces a novel approach to localizing and tracking other vehicles on the road with respect to lane position, which provides information on higher contextual relevance that neither the lane tracker nor vehicle tracker can provide by itself.
Improvements in lane tracking and vehicle tracking have been extensively quantified. Integrated system performance has been validated on real-world highway data. Without specific hardware and software optimizations, the fully implemented system runs at near-real-time speeds of 11 frames per second.
Intelligent Household LED Lighting System Considering Energy Efficiency and User Satisfaction
Saving energy has become one of the most important issues these days. The most waste of energy is caused by the inefficient use of the consumer electronics. Particularly, a light accounts for a great part of the total energy consumption.
Various light control systems are introduced in current markets, because the installed lighting systems are outdated and energy-inefficient. However, due to architectural limitations, the existing light control systems cannot be successfully applied to home and office buildings. Therefore, this paper proposes an intelligent household LED lighting system considering energy efficiency and user satisfaction.
The proposed system utilizes multi sensors and wireless communication technology in order to control an LED light according to the user's state and the surroundings. The proposed LED lighting system can autonomously adjust the minimum light intensity value to enhance both energy efficiency and user satisfaction.
We designed and implemented the proposed system in the test bed and measured total power consumption to verify the performance. The proposed LED lighting system reduces total power consumption of the test bed up to 21.9%1
Various light control systems are introduced in current markets, because the installed lighting systems are outdated and energy-inefficient. However, due to architectural limitations, the existing light control systems cannot be successfully applied to home and office buildings. Therefore, this paper proposes an intelligent household LED lighting system considering energy efficiency and user satisfaction.
The proposed system utilizes multi sensors and wireless communication technology in order to control an LED light according to the user's state and the surroundings. The proposed LED lighting system can autonomously adjust the minimum light intensity value to enhance both energy efficiency and user satisfaction.
We designed and implemented the proposed system in the test bed and measured total power consumption to verify the performance. The proposed LED lighting system reduces total power consumption of the test bed up to 21.9%1
Intelligent Traffic Signal Control Using Wireless Sensor Networks
Typical intelligent transportation systems (ITS) are comprised of geographically distributed ITS devices including sensors, cameras and dynamic message signs (DMS). There are several options for providing data communication between these field devices and traffic management centers (TMC). Wireless networks are attractive due to their relatively lower cost and ease of deployment compared to fixed networks.
However, these face unique security and signal interference problems, and deploying new wireless networks can require significant equipment investment. In this work, a new extremely low-cost wireless strategy for ITS network communication is presented.
This approach applies control channels of the Network Trunking System (NTS), a licensed radio frequency to support the voice communication, to control DMS operation under the National Transportation Communications for ITS Protocol (NTCIP). Because the NTS network has already installed in the metropolitan, urban, and rural areas in Oklahoma, it provides a cheap deployment solution requiring only additional adapter devices.
Long term operation and maintenance costs can further be amortized between voice and data services. The proposed technique is compared to the existing ITS wireless networking strategies and hybrid network strategies merging wired and wireless networks deployed in Oklahoma. Details of the strategy for using wireless networking in the Oklahoma ITS and experiences with wireless ITS device deployment are also provided.
However, these face unique security and signal interference problems, and deploying new wireless networks can require significant equipment investment. In this work, a new extremely low-cost wireless strategy for ITS network communication is presented.
This approach applies control channels of the Network Trunking System (NTS), a licensed radio frequency to support the voice communication, to control DMS operation under the National Transportation Communications for ITS Protocol (NTCIP). Because the NTS network has already installed in the metropolitan, urban, and rural areas in Oklahoma, it provides a cheap deployment solution requiring only additional adapter devices.
Long term operation and maintenance costs can further be amortized between voice and data services. The proposed technique is compared to the existing ITS wireless networking strategies and hybrid network strategies merging wired and wireless networks deployed in Oklahoma. Details of the strategy for using wireless networking in the Oklahoma ITS and experiences with wireless ITS device deployment are also provided.
Introduction of electromagnetic image-based chipless RFID system
All available techniques in chipless RFID systems are suffering from low data capacity. In this paper electromagnetic imaging technique in mm-wave range is proposed to enhance low data capacity of chipless RFID tags. It is shown through simulation that the diffraction of electromagnetic waves by a well oriented narrow conductive strip suggests a reliable approach for data encoding in the proposed technique.
The proposed technique is capable of coding 2 bit/cm2 in only 100 MHz of frequency bandwidth. Synthetic Aperture Radar technique is also proposed to provide a high resolution image and solving the problem of farfield limitation of the reader antenna.
The proposed technique is capable of coding 2 bit/cm2 in only 100 MHz of frequency bandwidth. Synthetic Aperture Radar technique is also proposed to provide a high resolution image and solving the problem of farfield limitation of the reader antenna.
LabVIEW-base automatic rising and falling Speed Control of Stepper Motor
Stepper motor is widely used as controlling and driving machine in opening loop controlling system. As high speed moving, stepper motor must have rising and falling process avoiding losing step and over step.
In this paper, based on analyzing and comparing some controlling graph, it gives a LabVIEW-based stepper motor control method and the composition of the control system, and making the soft controlling of stepper motor's automatic rising and falling speed come true.
Comparing with the single-chip controlled stepper motor, this system based on LabVIEW has a good interface, the easy programming to effective control, that is the practical application value.
In this paper, based on analyzing and comparing some controlling graph, it gives a LabVIEW-based stepper motor control method and the composition of the control system, and making the soft controlling of stepper motor's automatic rising and falling speed come true.
Comparing with the single-chip controlled stepper motor, this system based on LabVIEW has a good interface, the easy programming to effective control, that is the practical application value.
LOBOT Low-Cost, Self-Contained Localization of Small-Sized Ground Robotic Vehicles
It is often important to obtain the real-time location of a small-sized ground robotic vehicle when it performs autonomous tasks either indoors or outdoors. We propose and implement LOBOT, a low-cost, self-contained localization system for small-sized ground robotic vehicles.
LOBOT provides accurate real-time, 3D positions in both indoor and outdoor environments. Unlike other localization schemes, LOBOT does not require external reference facilities, expensive hardware, careful tuning or strict calibration, and is capable of operating under various indoor and outdoor environments.
LOBOT identifies the local relative movement through a set of integrated inexpensive sensors and well corrects the localization drift by infrequent GPS-augmentation. Our empirical experiments in various temporal and spatial scales show that LOBOT keeps the positioning error well under an accepted threshold.
LOBOT provides accurate real-time, 3D positions in both indoor and outdoor environments. Unlike other localization schemes, LOBOT does not require external reference facilities, expensive hardware, careful tuning or strict calibration, and is capable of operating under various indoor and outdoor environments.
LOBOT identifies the local relative movement through a set of integrated inexpensive sensors and well corrects the localization drift by infrequent GPS-augmentation. Our empirical experiments in various temporal and spatial scales show that LOBOT keeps the positioning error well under an accepted threshold.
Low Power Wireless Sensor Network for Building Monitoring
A wireless sensor network is proposed for monitoring buildings to assess earthquake damage. The sensor nodes use custom-developed capacitive microelectromechanical systems strain and 3-D acceleration sensors and a low power readout application-specified integrated circuit for a battery life of up to 12 years. The strain sensors are mounted at the base of the building to measure the settlement and plastic hinge activation of the building after an earthquake.
They measure periodically or on-demand from the base station. The accelerometers are mounted at every floor of the building to measure the seismic response of the building during an earthquake. They record during an earthquake event using a combination of the local acceleration data and remote triggering from the base station based on the acceleration data from multiple sensors across the building.
A low power network architecture was implemented over an 802.15.4 MAC in the 900-MHz band. A custom patch antenna was designed in this frequency band to obtain robust links in real-world conditions. The modules have been validated in a full-scale laboratory setup with simulated earthquakes.
They measure periodically or on-demand from the base station. The accelerometers are mounted at every floor of the building to measure the seismic response of the building during an earthquake. They record during an earthquake event using a combination of the local acceleration data and remote triggering from the base station based on the acceleration data from multiple sensors across the building.
A low power network architecture was implemented over an 802.15.4 MAC in the 900-MHz band. A custom patch antenna was designed in this frequency band to obtain robust links in real-world conditions. The modules have been validated in a full-scale laboratory setup with simulated earthquakes.
Management of Mechanical Vibration and Temperature in Small Wind Turbines using Zigbee Wireless Network
This paper presents the development of a methodology to manage the mechanic vibration and temperature from Small Wind Turbine (SWT). The objective with this research is propose a new diagnostic and protection tool through analysis and monitoring signals of vibration and temperature from wind turbines, aiming predict a need of preventive maintenance and mostly avoids catastrophic failures.
For this feature the system will be composed of a Triple Axis accelerometer who will identify vibration, thermocouples to identify the temperatures at critical points of wind turbine, a microcontroller hardware which will make acquisition and processing of signals from sensors and finally a wireless transmission system using technology ZigBee.
The post processing is performed remotely through a computer that receives the data submitted via wireless network presenting them to the user via graphical interface. The software of User friendly interface will have the functionality plus online display of received data also the possibility of storing and reporting data rates of vibration and temperature obtained during monitoring. Finally featuring the prototype of the hardware and software as well as some results obtained in experimental scale.
For this feature the system will be composed of a Triple Axis accelerometer who will identify vibration, thermocouples to identify the temperatures at critical points of wind turbine, a microcontroller hardware which will make acquisition and processing of signals from sensors and finally a wireless transmission system using technology ZigBee.
The post processing is performed remotely through a computer that receives the data submitted via wireless network presenting them to the user via graphical interface. The software of User friendly interface will have the functionality plus online display of received data also the possibility of storing and reporting data rates of vibration and temperature obtained during monitoring. Finally featuring the prototype of the hardware and software as well as some results obtained in experimental scale.
Maximum Power Point Tracking Employing Sliding Mode Control
A fast and unconditionally stable maximum power point tracking scheme with high tracking efficiency is proposed for photovoltaic generators. The fast dynamics and all range stability are attained by a sliding mode control and the high tracking efficiency by a maximum power point algorithm with fine step.
In response to a sudden change in radiation, our experiments show a typical convergence time of 15 ms. This is the fastest convergence time reported to date. In addition we demonstrate stable convergence all across the photovoltaic curve, from short-circuit to open-circuit. The theory is validated experimentally.
In response to a sudden change in radiation, our experiments show a typical convergence time of 15 ms. This is the fastest convergence time reported to date. In addition we demonstrate stable convergence all across the photovoltaic curve, from short-circuit to open-circuit. The theory is validated experimentally.
Mobile robot localization using the phase of passive UHF-RFID signals
This paper presents a global localization system for an indoor autonomous vehicle equipped with odometry sensors and a radio-frequency identification (RFID) reader to interrogate tags located on the ceiling of the environment.
The RFID reader can measure the phase of the signals coming from responding tags. This phase has non-univocal dependence on the distance robot tag, but in the considered frequency, it is really sensitive to a change in the position of the robot.
For this reason, a multihypothesis Kalman filtering approach provides a really satisfactory performance even in the case that a very small density of tags is used: In the experimental tests, an average position estimation error of about 4 cm is achieved using only two tags for an area of about 5 $hbox{m}^{2}$.
The RFID reader can measure the phase of the signals coming from responding tags. This phase has non-univocal dependence on the distance robot tag, but in the considered frequency, it is really sensitive to a change in the position of the robot.
For this reason, a multihypothesis Kalman filtering approach provides a really satisfactory performance even in the case that a very small density of tags is used: In the experimental tests, an average position estimation error of about 4 cm is achieved using only two tags for an area of about 5 $hbox{m}^{2}$.
Modeling Object Flows from Distributed and Federated RFID Data Streams for Efficient Tracking and Tracing
In the emerging environment of the Internet of Things (IoT), through the connection of billions of radio frequency identification (RFID) tags and sensors to the Internet, applications will generate an unprecedented number of transactions and amount of data that require novel approaches in RFID data stream processing and management.
Unfortunately, it is difficult to maintain a distributed model without a shared directory or structured index. In this paper, we propose a fully distributed model for sovereign RFID data streams. This model combines two techniques namely, Tilted Time Frame and Histogram to represent the patterns of object flows.
Our model is efficient in space and can be stored in main memory. The model is built on top of an unstructured P2P overlay. To reduce the overhead of distributed data acquisition, we further propose several algorithms that use a statistically minimum number of network calls to maintain the model. The scalability and efficiency of the proposed model are demonstrated through an extensive set of experiments.
Unfortunately, it is difficult to maintain a distributed model without a shared directory or structured index. In this paper, we propose a fully distributed model for sovereign RFID data streams. This model combines two techniques namely, Tilted Time Frame and Histogram to represent the patterns of object flows.
Our model is efficient in space and can be stored in main memory. The model is built on top of an unstructured P2P overlay. To reduce the overhead of distributed data acquisition, we further propose several algorithms that use a statistically minimum number of network calls to maintain the model. The scalability and efficiency of the proposed model are demonstrated through an extensive set of experiments.
Monitoring of cigarette smoking using wearable sensors and Support Vector Machines
Cigarette smoking is a serious risk factor for cancer, cardiovascular, and pulmonary diseases. Current methods of monitoring of cigarette smoking habits rely on various forms of self-report that are prone to errors and under reporting.
This paper presents a first step in the development of a methodology for accurate and objective assessment of smoking using noninvasive wearable sensors (Personal Automatic Cigarette Tracker - PACT) by demonstrating feasibility of automatic recognition of smoke inhalations from signals arising from continuous monitoring of breathing and hand-to-mouth gestures by support vector machine classifiers. The performance of subject-dependent (individually calibrated) models was compared to performance of subject-independent (group) classification models.
The models were trained and validated on a dataset collected from 20 subjects performing 12 different activities representative of everyday living (total duration 19.5 h or 21411 breath cycles). Precision and recall were used as the accuracy metrics. Group models obtained 87% and 80% of average precision and recall, respectively.
Individual models resulted in 90% of average precision and recall, indicating a significant presence of individual traits in signal patterns. These results suggest the feasibility of monitoring cigarette smoking by means of a wearable and noninvasive sensor system in free living conditions.
This paper presents a first step in the development of a methodology for accurate and objective assessment of smoking using noninvasive wearable sensors (Personal Automatic Cigarette Tracker - PACT) by demonstrating feasibility of automatic recognition of smoke inhalations from signals arising from continuous monitoring of breathing and hand-to-mouth gestures by support vector machine classifiers. The performance of subject-dependent (individually calibrated) models was compared to performance of subject-independent (group) classification models.
The models were trained and validated on a dataset collected from 20 subjects performing 12 different activities representative of everyday living (total duration 19.5 h or 21411 breath cycles). Precision and recall were used as the accuracy metrics. Group models obtained 87% and 80% of average precision and recall, respectively.
Individual models resulted in 90% of average precision and recall, indicating a significant presence of individual traits in signal patterns. These results suggest the feasibility of monitoring cigarette smoking by means of a wearable and noninvasive sensor system in free living conditions.
Online Monitoring of Geological CO2 Storage and Leakage Based on Wireless Sensor Networks
A remote online carbon dioxide (CO2) concentration monitoring system is developed, based on the technologies of wireless sensor networks, in allusion to the gas leakage monitoring requirement for CO2 capture and storage.
The remote online CO2 monitoring system consists of monitoring equipment, a data center server, and the clients. The monitoring equipment is composed of a central processing unit (CPU), air environment sensors array, global positioning system (GPS) receiver module, secure digital memory card (SD) storage module, liquid crystal display (LCD) module, and general packet radio service (GPRS) wireless transmission module.
The sensors array of CO2, temperature, humidity, and light intensity are used to collect data and the GPS receiver module is adopted to collect location and time information. The CPU automatically stores the collected data in the SD card data storage module and displays them on the LCD display module in real-time. Afterwards, the GPRS module continuously wirelessly transmits the collected information to the data center server.
The online monitoring WebGIS clients are developed using a PHP programming language, which runs on the Apache web server. MySQL is utilized as the database because of its speed and reliability, and the stunning cross-browser web maps are created, optimized, and deployed with the OpenLayers JavaScript web-mapping library.
Finally, an experiment executed in Xuzhou city, Jiangsu province, China is introduced to demonstrate the implementation and application.
The remote online CO2 monitoring system consists of monitoring equipment, a data center server, and the clients. The monitoring equipment is composed of a central processing unit (CPU), air environment sensors array, global positioning system (GPS) receiver module, secure digital memory card (SD) storage module, liquid crystal display (LCD) module, and general packet radio service (GPRS) wireless transmission module.
The sensors array of CO2, temperature, humidity, and light intensity are used to collect data and the GPS receiver module is adopted to collect location and time information. The CPU automatically stores the collected data in the SD card data storage module and displays them on the LCD display module in real-time. Afterwards, the GPRS module continuously wirelessly transmits the collected information to the data center server.
The online monitoring WebGIS clients are developed using a PHP programming language, which runs on the Apache web server. MySQL is utilized as the database because of its speed and reliability, and the stunning cross-browser web maps are created, optimized, and deployed with the OpenLayers JavaScript web-mapping library.
Finally, an experiment executed in Xuzhou city, Jiangsu province, China is introduced to demonstrate the implementation and application.
Passenger alerts system for easy navigation of blind
Talking signs, guide cane, echolocations are all useful in navigating the visually challenged people to reach their destination, but the main objective is not reached that it fails to join them with traffic. In this project we propose a bus system using wireless sensor networks (WSNs). The blind people in the bus station is provided with a ZigBee unit which is recognized by the ZigBee in the bus and the indication is made in the bus that the blind people is present in the station.
So the bus stops at the particular station. The desired bus that the blind want to take is notified to him with the help of speech recognition system HM2007. The blind gives the input about the place he has to reach using microphones and the voice recognition system recognizes it. The input is then analyzed by the microcontroller which generates the bus numbers corresponding to the location provided by the blind.
These bus numbers are converted into audio output using the voice synthesizer APR 9600. The ZigBee transceiver in the bus sends the bus number to the transceiver with the blind and the bus number is announced to the blind through the headphones.
The blind takes the right bus parked in front of him and when the destination is reached it is announced by means of the GPS-634R which is connected with the controller and voice synthesizer which produces the audio output. This project is also aimed at helping the elder people for independent navigation.
So the bus stops at the particular station. The desired bus that the blind want to take is notified to him with the help of speech recognition system HM2007. The blind gives the input about the place he has to reach using microphones and the voice recognition system recognizes it. The input is then analyzed by the microcontroller which generates the bus numbers corresponding to the location provided by the blind.
These bus numbers are converted into audio output using the voice synthesizer APR 9600. The ZigBee transceiver in the bus sends the bus number to the transceiver with the blind and the bus number is announced to the blind through the headphones.
The blind takes the right bus parked in front of him and when the destination is reached it is announced by means of the GPS-634R which is connected with the controller and voice synthesizer which produces the audio output. This project is also aimed at helping the elder people for independent navigation.
Portable wireless biomedical temperature monitoring system Architecture and implementation Architecture and Implementation Architecture and Implementation
This paper demonstrates the design and implementation of a portable embedded system targeting continuous temperature monitoring with wireless interface capability. Our main motive is to provide a solution for monitoring babies', disable or elderly population body temperature and initiate immediate alarm in case of hazardous cases.
Such cases include overheating (fever), under heating, and a high temperature change over a predefined time period. The advantage of the system is its effectiveness as preventive measure against febrile seizures or any other fever condition. The system is extended for interfacing with other devices such as cell phones to enable remote monitoring; an android application to showcase the concept was developed.
The system architecture consist of temperature sensors, LCD screen, Bluetooth interface, memory, a sound buzzer all controlled by a single microcontroller core. Even though the system is concentrated on temperature monitoring but the architecture can be expanded to monitor other vital signs like pulse rate, Oxygen saturation or any other interested parameter.
Such cases include overheating (fever), under heating, and a high temperature change over a predefined time period. The advantage of the system is its effectiveness as preventive measure against febrile seizures or any other fever condition. The system is extended for interfacing with other devices such as cell phones to enable remote monitoring; an android application to showcase the concept was developed.
The system architecture consist of temperature sensors, LCD screen, Bluetooth interface, memory, a sound buzzer all controlled by a single microcontroller core. Even though the system is concentrated on temperature monitoring but the architecture can be expanded to monitor other vital signs like pulse rate, Oxygen saturation or any other interested parameter.
Power Consumption in Direct Interface Circuits
This paper analyzes theoretically and experimentally the current consumption in direct interface circuits, i.e., circuits in which the sensor is directly connected to a microcontroller ( µC) without using either a signal conditioning circuit or an analog-to-digital converter.
The theoretical analysis, which takes into account the current consumed by both the internal electronics of the µC and the external components, proposes formulas to estimate the average current consumption in active mode. The estimated values fairly agree with those obtained in the experimental tests carried out by an AVR ATtiny2313 µC at different operating conditions.
For example, the current consumption in active mode at 3 V-4 MHz was about 1.5 mA for the measurement of a 1-kO resistive sensor and 0.6 mA for the measurement of a 177-pF capacitive sensor. The results reported herein are expected to be useful for the design of direct interface circuits intended for battery-powered measurement systems.
The theoretical analysis, which takes into account the current consumed by both the internal electronics of the µC and the external components, proposes formulas to estimate the average current consumption in active mode. The estimated values fairly agree with those obtained in the experimental tests carried out by an AVR ATtiny2313 µC at different operating conditions.
For example, the current consumption in active mode at 3 V-4 MHz was about 1.5 mA for the measurement of a 1-kO resistive sensor and 0.6 mA for the measurement of a 177-pF capacitive sensor. The results reported herein are expected to be useful for the design of direct interface circuits intended for battery-powered measurement systems.
Real-time indoor surveillance based on smartphone and mobile robot
The purpose of this study is to integrate image processing techniques, fuzzy theory, wireless communications, and smartphone to a wheeled mobile robot (WMR) for real-time object recognition, tracking and indoor surveillance. Image processing and fuzzy control algorithms are coded by C# language. Zigbee is utilized to transmit command signals between webcam, WMR, and computer.
The WMR uses webcam to capture its surroundings. Classification of color features is based on Hue-Saturation-Value (HSV) color space. The WMR calculates the relative position of the target object through image processing and distance computation algorithms. Fuzzy system is applied to servo motor of the WMR and robot controller design. The WMR is applied to surveillance usage, it can be controlled remotely by a smartphone via WIFI and perform indoor patrol and monitor its surroundings.
The home site conditions can be clearly seen on the smartphone. Experiments show that the proposed control design and system integration of the wheeled mobile robot works well in indoor real-time surveillance.
The WMR uses webcam to capture its surroundings. Classification of color features is based on Hue-Saturation-Value (HSV) color space. The WMR calculates the relative position of the target object through image processing and distance computation algorithms. Fuzzy system is applied to servo motor of the WMR and robot controller design. The WMR is applied to surveillance usage, it can be controlled remotely by a smartphone via WIFI and perform indoor patrol and monitor its surroundings.
The home site conditions can be clearly seen on the smartphone. Experiments show that the proposed control design and system integration of the wheeled mobile robot works well in indoor real-time surveillance.
Remote Monitoring System of ECG and Body Temperature Signals
The paper presents a remote monitoring system for electrocardiographic and temperature signals. The system consists of a hardware module for acquisition, a Bluetooth transmission module and finally a displaying module (PC or mobile devices).
Information is sent via IP (GPRS or WiFi) to a database server containing clinical data, which can be accessed through a web application. The system was assessed by testing different patients with the support of a medical doctor, obtaining a positive performance.
Information is sent via IP (GPRS or WiFi) to a database server containing clinical data, which can be accessed through a web application. The system was assessed by testing different patients with the support of a medical doctor, obtaining a positive performance.
Remote-Control System of High Efficiency and Intelligent Street Lighting Using a ZigBee Network of Devices and Sensors
The proposed remote-control system can optimize management and efficiency of street lighting systems. It uses ZigBee-based wireless devices which enable more efficient street lamp-system management, thanks to an advanced interface and control architecture.
It uses a sensor combination to control and guarantee the desired system parameters; the information is transferred point by point using ZigBee transmitters and receivers and is sent to a control terminal used to check the state of the street lamps and to take appropriate measures in case of failure.
It uses a sensor combination to control and guarantee the desired system parameters; the information is transferred point by point using ZigBee transmitters and receivers and is sent to a control terminal used to check the state of the street lamps and to take appropriate measures in case of failure.
RFID range extension with low-power wireless edge devices
Coverage area is an important performance metric for RFID systems, especially those used for inventory management. As such, there are a range of methods being developed to try to increase the coverage area of RFID systems without requiring additional costly and power hungry RFID readers. Most existing approaches to increase coverage employ RFID readers with multiple antennas, but this creates problems in deployment and in the timing of the RFID tag reads from the different antennas.
In this paper, we propose a different approach to extend the coverage area of a single reader, using a ZigBee-based, battery-operated device we call an edge device to cooperate with the RFID reader on reading the RFID tags. The edge device is also compatible with existing RFID range extension methods for additional increase in coverage. We implement an edge device hardware platform and evaluate the performance of the system in terms of coverage extension, and we provide estimates of the lifetime achievable for different tag access scenarios.
Our experiments show that each low cost, easily deployable edge device can increase the coverage area by about 70 %, and that they last for about 1.5 months if the tags are accessed twice an hour to upwards of 4 years if they are accessed once a day, as is sufficient for many inventory management applications.
In this paper, we propose a different approach to extend the coverage area of a single reader, using a ZigBee-based, battery-operated device we call an edge device to cooperate with the RFID reader on reading the RFID tags. The edge device is also compatible with existing RFID range extension methods for additional increase in coverage. We implement an edge device hardware platform and evaluate the performance of the system in terms of coverage extension, and we provide estimates of the lifetime achievable for different tag access scenarios.
Our experiments show that each low cost, easily deployable edge device can increase the coverage area by about 70 %, and that they last for about 1.5 months if the tags are accessed twice an hour to upwards of 4 years if they are accessed once a day, as is sufficient for many inventory management applications.
Sensing Devices and Sensor Signal Processing for Remote Monitoring of Vital Signs in CHF Patients
Nowadays, chronic heart failure (CHF) affects an ever-growing segment of population, and it is among the major causes of hospitalization for elderly citizens. The actual out-of-hospital treatment model, based on periodic visits, has a low capability to detect signs of destabilization and leads to a high re-hospitalization rate.
To this aim, in this paper, a complete and integrated Information and Communication Technology system is described enabling the CHF patients to daily collect vital signs at home and automatically send them to the Hospital Information System, allowing the physicians to monitor their patients at distance and take timely actions in case of necessity.
A minimum set of vital parameters has been identified, consisting of electrocardiogram, SpO2, blood pressure, and weight, measured through a pool of wireless, non-invasive biomedical sensors. A multi-channel front-end IC for cardiac sensor interfacing has been also developed. Sensor data acquisition and signal processing are in charge of an additional device, the home gateway.
All signals are processed upon acquisition in order to assert if both punctual values and extracted trends lay in a safety zone established by thresholds. Per-patient personalized thresholds, required measurements and transmission policy are allowed.
As proved by first medical tests, the proposed telemedicine platform represents a valid support to early detect the alterations in vital signs that precede the acute syndromes, allowing early home interventions thus reducing the number of subsequent hospitalizations.
To this aim, in this paper, a complete and integrated Information and Communication Technology system is described enabling the CHF patients to daily collect vital signs at home and automatically send them to the Hospital Information System, allowing the physicians to monitor their patients at distance and take timely actions in case of necessity.
A minimum set of vital parameters has been identified, consisting of electrocardiogram, SpO2, blood pressure, and weight, measured through a pool of wireless, non-invasive biomedical sensors. A multi-channel front-end IC for cardiac sensor interfacing has been also developed. Sensor data acquisition and signal processing are in charge of an additional device, the home gateway.
All signals are processed upon acquisition in order to assert if both punctual values and extracted trends lay in a safety zone established by thresholds. Per-patient personalized thresholds, required measurements and transmission policy are allowed.
As proved by first medical tests, the proposed telemedicine platform represents a valid support to early detect the alterations in vital signs that precede the acute syndromes, allowing early home interventions thus reducing the number of subsequent hospitalizations.
Sitting posture detection and recognition using force sensor
This paper presents an architecture for information capture and analysis of sitting posture using force sensor. We utilize force sensor and microcontroller to build a system for force information. We fix positions of force sensors on seat cushions firstly.
Then, we design the circuits on microcontroller and obtain the data from sensors. There are different types of information in deferent sitting postures. We analyze and categorize the information for recognizing the sitting postures.
This system could be utilized to detect the incorrect sitting postures for children, patients or elder people in the future.
Then, we design the circuits on microcontroller and obtain the data from sensors. There are different types of information in deferent sitting postures. We analyze and categorize the information for recognizing the sitting postures.
This system could be utilized to detect the incorrect sitting postures for children, patients or elder people in the future.
Smart Host Microcontroller for Optimal Battery Charging in a Solar-Powered Robotic Vehicle
This paper focuses on the design and construction of an optimization charging system for Li-Po batteries by means of tracked solar panels. Thus, the implementation of a complete energy management system applied to a robotic exploration vehicle is put forward.
The proposed system was tested on the VANTER robotic platform-an autonomous unmanned exploration vehicle specialized in recognition. The interest of this robotic system lies in the design concept, based on a smart host microcontroller.
On this basis, our proposal makes a twofold significant contribution. On the one hand, it presents the construction of a solar tracking mechanism aimed at increasing the rover's power regardless of its mobility.
On the other hand, it proposes an alternative design of power system performance based on a pack of two batteries. The aim is completing the process of charging a battery independently while the other battery provides all the energy consumed by the robotic vehicle.
The proposed system was tested on the VANTER robotic platform-an autonomous unmanned exploration vehicle specialized in recognition. The interest of this robotic system lies in the design concept, based on a smart host microcontroller.
On this basis, our proposal makes a twofold significant contribution. On the one hand, it presents the construction of a solar tracking mechanism aimed at increasing the rover's power regardless of its mobility.
On the other hand, it proposes an alternative design of power system performance based on a pack of two batteries. The aim is completing the process of charging a battery independently while the other battery provides all the energy consumed by the robotic vehicle.
Solar powered water quality monitoring system using wireless sensor network
The idea of `Underwater Wireless Sensor Network' (UWSN) is the basic building block of a water quality monitoring using wireless sensor network (WSN) technology powered by solar panel. To monitor water quality over different sites as a real-time application, an excellent system architecture constituted by distributed sensor nodes and a base station is suggested.
The nodes and base station are connected using WSN technology like Zigbee. Design and implementation of a prototype model using one node powered by solar cell and WSN technology is the challenging work. Data collected by various sensors at the node side such as pH, turbidity and oxygen level is sent via WSN to the base station.
Data collected from the remote site can be displayed in visual format as well as it can be analyzed using different simulation tools at base station. This novel system has advantages such as no carbon emission, low power consumption, more flexible to deploy at remote site and so on.
The nodes and base station are connected using WSN technology like Zigbee. Design and implementation of a prototype model using one node powered by solar cell and WSN technology is the challenging work. Data collected by various sensors at the node side such as pH, turbidity and oxygen level is sent via WSN to the base station.
Data collected from the remote site can be displayed in visual format as well as it can be analyzed using different simulation tools at base station. This novel system has advantages such as no carbon emission, low power consumption, more flexible to deploy at remote site and so on.
The Intelligent CoPilot - A Constraint-Based Approach to Shared-Adaptive Control of Ground Vehicles
This work presents a new approach to semi-autonomous vehicle hazard avoidance and stability control, based on the design and selective enforcement of constraints. This differs from traditional approaches that rely on the planning and tracking of paths and facilitates "minimally-invasive" control for human-machine systems.
Instead of forcing a human operator to follow an automation-determined path, the constraint-based approach identifies safe homotopies, and allows the operator to navigate freely within them, introducing control action only as necessary to ensure that the vehicle does not violate safety constraints.
This method evaluates candidate homotopies based on "restrictiveness," rather than traditional measures of path goodness, and designs and enforces requisite constraints on the human's control commands to ensure that the vehicle never leaves the controllable subset of a desired homotopy.
This paper demonstrates the approach in simulation and characterizes its effect on human teleoperation of unmanned ground vehicles via a 20-user, 600-trial study on an outdoor obstacle course. Aggregated across all drivers and experiments, the constraint based control system required an average of 43% of the available control authority to reduce collision frequency by 78% relative to traditional teleoperation, increase average speed by 26%, and moderate operator steering commands by 34%.
Instead of forcing a human operator to follow an automation-determined path, the constraint-based approach identifies safe homotopies, and allows the operator to navigate freely within them, introducing control action only as necessary to ensure that the vehicle does not violate safety constraints.
This method evaluates candidate homotopies based on "restrictiveness," rather than traditional measures of path goodness, and designs and enforces requisite constraints on the human's control commands to ensure that the vehicle never leaves the controllable subset of a desired homotopy.
This paper demonstrates the approach in simulation and characterizes its effect on human teleoperation of unmanned ground vehicles via a 20-user, 600-trial study on an outdoor obstacle course. Aggregated across all drivers and experiments, the constraint based control system required an average of 43% of the available control authority to reduce collision frequency by 78% relative to traditional teleoperation, increase average speed by 26%, and moderate operator steering commands by 34%.
The New Approach to RFID Assisted Navigation Systems for VANETs
This work presents a new approach to semi-autonomous vehicle hazard avoidance and stability control, based on the design and selective enforcement of constraints. This differs from traditional approaches that rely on the planning and tracking of paths and facilitates "minimally-invasive" control for human-machine systems.
Instead of forcing a human operator to follow an automation-determined path, the constraint-based approach identifies safe homotopies, and allows the operator to navigate freely within them, introducing control action only as necessary to ensure that the vehicle does not violate safety constraints.
This method evaluates candidate homotopies based on "restrictiveness," rather than traditional measures of path goodness, and designs and enforces requisite constraints on the human's control commands to ensure that the vehicle never leaves the controllable subset of a desired homotopy.
This paper demonstrates the approach in simulation and characterizes its effect on human teleoperation of unmanned ground vehicles via a 20-user, 600-trial study on an outdoor obstacle course. Aggregated across all drivers and experiments, the constraint based control system required an average of 43% of the available control authority to reduce collision frequency by 78% relative to traditional teleoperation, increase average speed by 26%, and moderate operator steering commands by 34%.
Instead of forcing a human operator to follow an automation-determined path, the constraint-based approach identifies safe homotopies, and allows the operator to navigate freely within them, introducing control action only as necessary to ensure that the vehicle does not violate safety constraints.
This method evaluates candidate homotopies based on "restrictiveness," rather than traditional measures of path goodness, and designs and enforces requisite constraints on the human's control commands to ensure that the vehicle never leaves the controllable subset of a desired homotopy.
This paper demonstrates the approach in simulation and characterizes its effect on human teleoperation of unmanned ground vehicles via a 20-user, 600-trial study on an outdoor obstacle course. Aggregated across all drivers and experiments, the constraint based control system required an average of 43% of the available control authority to reduce collision frequency by 78% relative to traditional teleoperation, increase average speed by 26%, and moderate operator steering commands by 34%.
The Ultrasonic Distance Alarm System Based on MSP430F449
The principle ultrasonic distance measurement was introduced. Using Texas Instrument's micro controller MSP430F449 and ultrasonic sensor TCT40-16F, an ultrasonic measurement and alarm system with high precision was designed.
Adopting the method of MJ echo capture, the system can measure the distance well and truly, and can send the real-time distance data to the LCD screen of system. Once the distance was less than the setting value, the system would alarm immediately.
In addition, the system uses temperature sensor for temperature compensation, which effectively improves the ranging accuracy. Experimental results show that the system has high range accuracy, and can complete the distance measuring task in cars.
Adopting the method of MJ echo capture, the system can measure the distance well and truly, and can send the real-time distance data to the LCD screen of system. Once the distance was less than the setting value, the system would alarm immediately.
In addition, the system uses temperature sensor for temperature compensation, which effectively improves the ranging accuracy. Experimental results show that the system has high range accuracy, and can complete the distance measuring task in cars.
Towards the Implementation of IoT for Environmental Condition Monitoring in Homes
In this paper, we have reported an effective implementation for Internet of Things used for monitoring regular domestic conditions by means of low cost ubiquitous sensing system.
The description about the integrated network architecture and the interconnecting mechanisms for reliable measurement of parameters by smart sensors and transmission of data via internet is being presented. The longitudinal learning system was able to provide self-control mechanism for better operations of the devices in monitoring stage.
The framework of the monitoring system is based on combination of pervasive distributed sensing units, information system for data aggregation, reasoning and context awareness.
Results are encouraging as the reliability of sensing information transmission through the proposed integrated network architecture is 97%. The prototype was tested to generate real-time graphical information rather than a test bed scenario.
The description about the integrated network architecture and the interconnecting mechanisms for reliable measurement of parameters by smart sensors and transmission of data via internet is being presented. The longitudinal learning system was able to provide self-control mechanism for better operations of the devices in monitoring stage.
The framework of the monitoring system is based on combination of pervasive distributed sensing units, information system for data aggregation, reasoning and context awareness.
Results are encouraging as the reliability of sensing information transmission through the proposed integrated network architecture is 97%. The prototype was tested to generate real-time graphical information rather than a test bed scenario.
Vertical Edge based Car License Plate Detection Method
This paper proposes a fast method for car-license-plate detection (CLPD) and presents three main contributions. The first contribution is that we propose a fast vertical edge detection algorithm (VEDA) based on the contrast between the grayscale values, which enhances the speed of the CLPD method.
After binarizing the input image using adaptive thresholding (AT), an unwanted-line elimination algorithm (ULEA) is proposed to enhance the image, and then, the VEDA is applied. The second contribution is that our proposed CLPD method processes very-low-resolution images taken by a web camera. After the vertical edges have been detected by the VEDA, the desired plate details based on color information are highlighted. Then, the candidate region based on statistical and logical operations will be extracted.
Finally, an LP is detected. The third contribution is that we compare the VEDA to the Sobel operator in terms of accuracy, algorithm complexity, and processing time. The results show accurate edge detection performance and faster processing than Sobel by five to nine times.
In terms of complexity, a big-O-notation module is used and the following result is obtained: The VEDA has less complexity by K2 times, whereas K2 represents the mask size of Sobel. Results show that the computation time of the CLPD method is 47.7 ms, which meets the real-time requirements.
After binarizing the input image using adaptive thresholding (AT), an unwanted-line elimination algorithm (ULEA) is proposed to enhance the image, and then, the VEDA is applied. The second contribution is that our proposed CLPD method processes very-low-resolution images taken by a web camera. After the vertical edges have been detected by the VEDA, the desired plate details based on color information are highlighted. Then, the candidate region based on statistical and logical operations will be extracted.
Finally, an LP is detected. The third contribution is that we compare the VEDA to the Sobel operator in terms of accuracy, algorithm complexity, and processing time. The results show accurate edge detection performance and faster processing than Sobel by five to nine times.
In terms of complexity, a big-O-notation module is used and the following result is obtained: The VEDA has less complexity by K2 times, whereas K2 represents the mask size of Sobel. Results show that the computation time of the CLPD method is 47.7 ms, which meets the real-time requirements.
Wireless access control system based on IEEE 802.15.4
Access control systems are the main security mechanisms to control the access of environments. This paper describes about the implementation and deployment of wireless access control system for providing authorized access in a smart home environment.
It makes use of ZigBee and image processing technique to control the door lock. ZigBee enabled door lock module has been designed and developed. The image transfer over ZigBee network has been analyzed for different image size and the challenges involved in the face recognition module are discussed.
It makes use of ZigBee and image processing technique to control the door lock. ZigBee enabled door lock module has been designed and developed. The image transfer over ZigBee network has been analyzed for different image size and the challenges involved in the face recognition module are discussed.
Wireless Capsule Endoscope for Targeted Drug Delivery Mechanics and Design Considerations
This paper describes a platform to achieve targeted drug delivery in the next-generation wireless capsule endoscopy. The platform consists of two highly novel subsystems: one is a micropositioning mechanism which can deliver 1 ml of targeted medication and the other is a holding mechanism, which gives the functionality of resisting peristalsis.
The micropositioning mechanism allows a needle to be positioned within a 22.5° segment of a cylindrical capsule and be extendible by up to 1.5 mm outside the capsule body. The mechanism achieves both these functions using only a single micromotor and occupying a total volume of just 200 mm3.
The holding mechanism can be deployed diametrically opposite the needle in 1.8 s and occupies a volume of just 270 mm3. An in-depth analysis of the mechanics is presented and an overview of the requirements necessary to realize a total system integration is discussed.
It is envisaged that the targeted drug delivery platform will empower a new breed of capsule microrobots for therapy in addition to diagnostics for pathologies such as ulcerative colitis and small intestinal Crohn's disease.
The micropositioning mechanism allows a needle to be positioned within a 22.5° segment of a cylindrical capsule and be extendible by up to 1.5 mm outside the capsule body. The mechanism achieves both these functions using only a single micromotor and occupying a total volume of just 200 mm3.
The holding mechanism can be deployed diametrically opposite the needle in 1.8 s and occupies a volume of just 270 mm3. An in-depth analysis of the mechanics is presented and an overview of the requirements necessary to realize a total system integration is discussed.
It is envisaged that the targeted drug delivery platform will empower a new breed of capsule microrobots for therapy in addition to diagnostics for pathologies such as ulcerative colitis and small intestinal Crohn's disease.
Zigbee and ATmega32 based wireless digital control and monitoring system For LED lighting
As the world population grows, energy consumption is increasing, widening is the power deficiency. This creates more demand for energy efficient devices in the market. The lighting systems that are widely being used now do not employ any control energy utilization.
In this paper we present wireless embedded control that can be used for both indoor lighting as well as outdoor lighting to switch on/off the lights and as well to reduce the light intensity of LED light which can reduce the power consumption effectively.
This improves energy efficiency of the lighting system as well as provides a sophisticated control over the energy consumption of the system.
In this paper we present wireless embedded control that can be used for both indoor lighting as well as outdoor lighting to switch on/off the lights and as well to reduce the light intensity of LED light which can reduce the power consumption effectively.
This improves energy efficiency of the lighting system as well as provides a sophisticated control over the energy consumption of the system.
Zigbee Based Intelligent Driver Assistance System
Driving always involves risk. Various means have been proposed to reduce the risk. Critical motion detection of nearby moving vehicles is one of the important means of preventing accidents.
In this paper, a computational model, which is referred to as the dynamic visual model (DVM), is proposed to detect critical motions of nearby vehicles while driving on a highway. The DVM is motivated by the human visual system and consists of three analyzers: 1) sensory analyzers, 2) perceptual analyzers, and 3) conceptual analyzers. In addition, a memory, which is called the episodic memory, is incorporated, through which a number of features of the system, including hierarchical processing, configurability, adaptive response, and selective attention, are realized.
A series of experimental results with both single and multiple critical motions are demonstrated and show the feasibility of the proposed system.
In this paper, a computational model, which is referred to as the dynamic visual model (DVM), is proposed to detect critical motions of nearby vehicles while driving on a highway. The DVM is motivated by the human visual system and consists of three analyzers: 1) sensory analyzers, 2) perceptual analyzers, and 3) conceptual analyzers. In addition, a memory, which is called the episodic memory, is incorporated, through which a number of features of the system, including hierarchical processing, configurability, adaptive response, and selective attention, are realized.
A series of experimental results with both single and multiple critical motions are demonstrated and show the feasibility of the proposed system.
A Battery Less Remote Control
In this paper we present a study on the feasibility of a wirelessly-powered battery-less remote control system. Such system, that is based on a passive multi-RFID scheme, has been recently proposed as an eco-friendly alternative to conventional infrared battery-assisted technology.
The proposed remote control unit does not require batteries and it is remotely powered by an RFID reader which is embedded in the device to be controlled (e.g. a TV). However, some questions related to cost effectiveness, feasibility and safety have been posed.
Accordingly, we discuss these issues and we propose strategies to optimize the system performance. The extent of the presented study covers also general Wireless Power Transmission Systems, especially in which concerns user safety (maximum exposure levels).
The proposed remote control unit does not require batteries and it is remotely powered by an RFID reader which is embedded in the device to be controlled (e.g. a TV). However, some questions related to cost effectiveness, feasibility and safety have been posed.
Accordingly, we discuss these issues and we propose strategies to optimize the system performance. The extent of the presented study covers also general Wireless Power Transmission Systems, especially in which concerns user safety (maximum exposure levels).
A CAN Bus based system for monitoring and fault diagnosis in Wind Turbine
Electrical energy can be produced using fossil fuels and also by natural resources. The production of electrical energy using fossil fuels is costlier when compared to natural resources.
Solar, wind, thermal and tidal energy are most widely used natural resources for the production of electrical energy. Presently wind energy is most widely used natural resources which could reduce the emission of carbon dioxide. The cost of the wind turbine is extremely higher and work in harsh and unattended environment.
Hence the monitoring and the automation of wind turbine are necessary. This paper describes the monitoring and fault diagnosis system for wind turbine using CAN interface. The monitoring parameters and CAN interface are described in detail.
Solar, wind, thermal and tidal energy are most widely used natural resources for the production of electrical energy. Presently wind energy is most widely used natural resources which could reduce the emission of carbon dioxide. The cost of the wind turbine is extremely higher and work in harsh and unattended environment.
Hence the monitoring and the automation of wind turbine are necessary. This paper describes the monitoring and fault diagnosis system for wind turbine using CAN interface. The monitoring parameters and CAN interface are described in detail.
A Compact and Compliant External Pipe-Crawling Robot
The focus of this paper is on the practical aspects of design, prototyping, and testing of a compact, compliant external pipe-crawling robot that can inspect a closely spaced bundle of pipes in hazardous environments and areas that are inaccessible to humans. The robot consists of two radially deployable compliant ring actuators that are attached to each other along the longitudinal axis of the pipe by a bidirectional linear actuator. The robot imitates the motion of an inchworm.
The novel aspect of the compliant ring actuator is a spring-steel compliant mechanism that converts circumferential motion to radial motion of its multiple gripping pads. Circumferential motion to ring actuators is provided by two shape memory alloy (SMA) wires that are guided by insulating rollers. The design of the compliant mechanism is derived from a radially deployable mechanism.
A unique feature of the design is that the compliant mechanism provides the necessary kinematic function within the limited annular space around the pipe and serves as the bias spring for the SMA wires. The robot has a control circuit that sequentially activates the SMA wires and the linear actuator; it also controls the crawling speed. The robot has been fabricated, tested, and automated.
Its crawling speed is about 45 mm/min, and the weight is about 150 g. It fits within an annular space of a radial span of 15 mm to crawl on a pipe of 60-mm outer diameter.
The novel aspect of the compliant ring actuator is a spring-steel compliant mechanism that converts circumferential motion to radial motion of its multiple gripping pads. Circumferential motion to ring actuators is provided by two shape memory alloy (SMA) wires that are guided by insulating rollers. The design of the compliant mechanism is derived from a radially deployable mechanism.
A unique feature of the design is that the compliant mechanism provides the necessary kinematic function within the limited annular space around the pipe and serves as the bias spring for the SMA wires. The robot has a control circuit that sequentially activates the SMA wires and the linear actuator; it also controls the crawling speed. The robot has been fabricated, tested, and automated.
Its crawling speed is about 45 mm/min, and the weight is about 150 g. It fits within an annular space of a radial span of 15 mm to crawl on a pipe of 60-mm outer diameter.
A Compact Remote Monitoring System for a Three-Phase 10-kVA Energy- Efficient Switchable Distribution Transformer
Remote monitoring has been implemented in many areas. This paper introduces its specific application to a three-phase 10-kVA energy-efficient switchable distribution transformer. A designed embedded system and embedded Ethernet have been implemented to achieve a compact remote condition monitoring for the transformer.
The embedded system performs acquisition of voltages, currents, and temperatures, controls the switching devices that connect the tappings of the transformer, and processes acquired data. Client and server applications were developed through the use of embedded Ethernet to enable remote monitoring through a local area network (LAN). Some protocols were developed as parts of software development of the whole system.
Experimentation was done by applying the remote monitoring system to the transformer connected to three-phase variable supply voltage and load. Results of the experimentation by using a LAN available in the school revealed that the system can handle remote monitoring and control tasks for the transformer.
The embedded system performs acquisition of voltages, currents, and temperatures, controls the switching devices that connect the tappings of the transformer, and processes acquired data. Client and server applications were developed through the use of embedded Ethernet to enable remote monitoring through a local area network (LAN). Some protocols were developed as parts of software development of the whole system.
Experimentation was done by applying the remote monitoring system to the transformer connected to three-phase variable supply voltage and load. Results of the experimentation by using a LAN available in the school revealed that the system can handle remote monitoring and control tasks for the transformer.
A Fatigue Detection System with Eyeglasses Removal
A fatigue detection system is designed to alert the driver and thus prevent the possible accidents. The detection is mainly based on the result of the face/eye detection or the pupil of the eyeball to determine whether the driver in the fatigue condition or not. Most of the previous studies assume that the driver does not wear the eyeglasses.
However, the eye detection is easily influenced by the eyeglasses and thus decreases the correct detection ratio. In order to overcome the influence of the eyeglasses, a fatigue detection method with eyeglass removal is proposed in this paper. Firstly, the face area is detected by using the functions in the OpenCV library.
Then, the eyeglasses are removed by using the morphological operations. After eyeglasses removal, the eye areas are detected by using the functions in the OpenCV library and tracking by using a template matching method. The binarization result of the eye area is performed the horizontal projection and Kalman filter. Then, the open/close state of eyes is determined, and then fatigue is determined based on the series state of eyes.
Four testing videos are used to evaluate the performance of the proposed method. The average correct detection ratio of the eye state is 88.5% and the fatigue detection can reach 100%. The preliminary results show that the proposed method is feasible.
However, the eye detection is easily influenced by the eyeglasses and thus decreases the correct detection ratio. In order to overcome the influence of the eyeglasses, a fatigue detection method with eyeglass removal is proposed in this paper. Firstly, the face area is detected by using the functions in the OpenCV library.
Then, the eyeglasses are removed by using the morphological operations. After eyeglasses removal, the eye areas are detected by using the functions in the OpenCV library and tracking by using a template matching method. The binarization result of the eye area is performed the horizontal projection and Kalman filter. Then, the open/close state of eyes is determined, and then fatigue is determined based on the series state of eyes.
Four testing videos are used to evaluate the performance of the proposed method. The average correct detection ratio of the eye state is 88.5% and the fatigue detection can reach 100%. The preliminary results show that the proposed method is feasible.
A Framework for Daily Activity Monitoring and Fall Detection Based on Surface Electromyography and Accelerometer Signals
As an essential branch of context awareness, activity awareness, especially daily activity monitoring and fall detection, is important to healthcare for the elderly and patients with chronic diseases. In this paper, a framework for activity awareness using surface electromyography and accelerometer (ACC) signals is proposed.
First, histogram negative entropy was employed to determine the start- and end-points of static and dynamic active segments. Then, the angle of each ACC axis was calculated to indicate body postures, which assisted with sorting dynamic activities into two categories: dynamic gait activities and dynamic transition ones, by judging whether the pre- and post-postures are both standing.
Next, the dynamic gait activities were identified by the double-stream hidden Markov models. Besides, the dynamic transition activities were distinguished into normal transition activities and falls by resultant ACC amplitude.
Finally, a continuous daily activity monitoring and fall detection scheme was performed with the recognition accuracy over 98%, demonstrating the excellent fall detection performance and the great feasibility of the proposed method in daily activities awareness.
First, histogram negative entropy was employed to determine the start- and end-points of static and dynamic active segments. Then, the angle of each ACC axis was calculated to indicate body postures, which assisted with sorting dynamic activities into two categories: dynamic gait activities and dynamic transition ones, by judging whether the pre- and post-postures are both standing.
Next, the dynamic gait activities were identified by the double-stream hidden Markov models. Besides, the dynamic transition activities were distinguished into normal transition activities and falls by resultant ACC amplitude.
Finally, a continuous daily activity monitoring and fall detection scheme was performed with the recognition accuracy over 98%, demonstrating the excellent fall detection performance and the great feasibility of the proposed method in daily activities awareness.
A friendly mobile Entertainment robot for disabled children
Disabled children, when compared to other children, have fewer opportunities for exploring and interacting with the world. Thus, they are exposed to the feeling that they are unable to do anything by themselves.
In this sense, the use of mobile robots may help these children to overcome their limitation and provide means to develop social skills. This paper describes partial results of on-going research on control architectures for mobile robots concerning hardware and software aspects.
We propose a behavior-based architecture for the interaction between humans and robots, particularly children with severe motor disabilities. The main goal is to create a modular, flexible and scalable development environment, which motivates children to interact with the robot and the world.
In this sense, the use of mobile robots may help these children to overcome their limitation and provide means to develop social skills. This paper describes partial results of on-going research on control architectures for mobile robots concerning hardware and software aspects.
We propose a behavior-based architecture for the interaction between humans and robots, particularly children with severe motor disabilities. The main goal is to create a modular, flexible and scalable development environment, which motivates children to interact with the robot and the world.
A Geometric Distribution Reader Anti-Collision Protocol for RFID Dense Reader Environments
Dense passive radio frequency identification (RFID) systems are particularly susceptible to reader collision problems, categorized by reader-to-tag and reader-to-reader collisions.
Both may degrade the system performance decreasing the number of identified tags per time unit. Although many proposals have been suggested to avoid or handle these collisions, most of them are not compatible with current standards and regulations, require extra hardware and do not make an efficient use of the network resources.
This paper proposes the Geometric Distribution Reader Anti-collision (GDRA), a new centralized scheduler that exploits the Sift geometric probability distribution function to minimize reader collision problems. GDRA provides higher throughput than the state-of-the-art proposals for dense reader environments and, unlike the majority of previous works, GDRA is compliant with the EPCglobal standard and ETSI EN 302 208 regulation, and can be implemented in real RFID systems without extra hardware.
Both may degrade the system performance decreasing the number of identified tags per time unit. Although many proposals have been suggested to avoid or handle these collisions, most of them are not compatible with current standards and regulations, require extra hardware and do not make an efficient use of the network resources.
This paper proposes the Geometric Distribution Reader Anti-collision (GDRA), a new centralized scheduler that exploits the Sift geometric probability distribution function to minimize reader collision problems. GDRA provides higher throughput than the state-of-the-art proposals for dense reader environments and, unlike the majority of previous works, GDRA is compliant with the EPCglobal standard and ETSI EN 302 208 regulation, and can be implemented in real RFID systems without extra hardware.
A Landslide Monitoring Technique based on Dual-Receiver & Phase Difference Measurements
A new landslide detection technique that installs a transmitter (Tx) array at the area of interest to transmit signals to two receivers is presented. It detects the phase difference change, due to the Tx displacement, at the dual-receiver system to monitor near real time of small but critical area landslide in centimeter range.
The dual-receiver system, apart at a small distance, demodulates the receiving signals independently but coherently. An ambiguity route, which corresponds to a landslide's movement without change on phase difference, is defined and must be avoided.
No field test was tried, but three simulatA Low-Complexity ECG Feature Extraction Algorithm for Mobile Healthcare Applicationsed examples are given to illustrate the technique.
The dual-receiver system, apart at a small distance, demodulates the receiving signals independently but coherently. An ambiguity route, which corresponds to a landslide's movement without change on phase difference, is defined and must be avoided.
No field test was tried, but three simulatA Low-Complexity ECG Feature Extraction Algorithm for Mobile Healthcare Applicationsed examples are given to illustrate the technique.
A Low-Complexity ECG Feature Extraction Algorithm for Mobile Healthcare Applications
This paper introduces a low-complexity algorithm for the extraction of the fiducial points from the electrocardiogram (ECG). The application area we consider is that of remote cardiovascular monitoring, where continuous sensing and processing takes place in low-power, computationally constrained devices, thus the power consumption and complexity of the processing algorithms should remain at a minimum level.
Under this context, we choose to employ the discrete wavelet transform (DWT) with the Haar function being the mother wavelet, as our principal analysis method. From the modulus-maxima analysis on the DWT coefficients, an approximation of the ECG fiducial points is extracted.
These initial findings are complimented with a refinement stage, based on the time-domain morphological properties of the ECG, which alleviates the decreased temporal resolution of the DWT. The resulting algorithm is a hybrid scheme of time- and frequency-domain signal processing. Feature extraction results from 27 ECG signals from QTDB were tested against manual annotations and used to compare our approach against the state-of-the art ECG delineators.
In addition, 450 signals from the 15-lead PTBDB are used to evaluate the obtained performance against the CSE tolerance limits. Our findings indicate that all but one CSE limits are satisfied. This level of performance combined with a complexity analysis, where the upper bound of the proposed algorithm, in terms of arithmetic operations, is calculated as $hbox{2.423}N+hbox{214}$ additions and $hbox{1.093}N+hbox{12}$ multiplications for $Nle hbox{861}$ or $hbox{2.553}N+hbox{102}$ additions and $hbox{1.093}N+hbox{10}$ multiplications for $N > hbox{861}$ ( $N$ being the number of input samples), reveals that the proposed method achieves an ideal tradeoff between computational complexity and performance, a key requirement in remote cardiovascular disease monitoring systems
Under this context, we choose to employ the discrete wavelet transform (DWT) with the Haar function being the mother wavelet, as our principal analysis method. From the modulus-maxima analysis on the DWT coefficients, an approximation of the ECG fiducial points is extracted.
These initial findings are complimented with a refinement stage, based on the time-domain morphological properties of the ECG, which alleviates the decreased temporal resolution of the DWT. The resulting algorithm is a hybrid scheme of time- and frequency-domain signal processing. Feature extraction results from 27 ECG signals from QTDB were tested against manual annotations and used to compare our approach against the state-of-the art ECG delineators.
In addition, 450 signals from the 15-lead PTBDB are used to evaluate the obtained performance against the CSE tolerance limits. Our findings indicate that all but one CSE limits are satisfied. This level of performance combined with a complexity analysis, where the upper bound of the proposed algorithm, in terms of arithmetic operations, is calculated as $hbox{2.423}N+hbox{214}$ additions and $hbox{1.093}N+hbox{12}$ multiplications for $Nle hbox{861}$ or $hbox{2.553}N+hbox{102}$ additions and $hbox{1.093}N+hbox{10}$ multiplications for $N > hbox{861}$ ( $N$ being the number of input samples), reveals that the proposed method achieves an ideal tradeoff between computational complexity and performance, a key requirement in remote cardiovascular disease monitoring systems
A Minimally Invasive Implantable Wireless Pressure Sensor for Continuous IOP Monitoring
This paper presents a minimally invasive implantable pressure sensing transponder for continuous wireless monitoring of intraocular pressure (IOP). The transponder is designed to make the implantation surgery simple while still measuring the true IOP through direct hydraulic contact with the intraocular space.
Furthermore, when IOP monitoring is complete, the design allows physicians to easily retrieve the transponder. The device consists of three main components: 1) a hypodermic needle (30 gauge) that penetrates the sclera through pars plana and establishes direct access to the vitreous space of the eye; 2) a micromachined capacitive pressure sensor connected to the needle back-end; and 3) a flexible polyimide coil connected to the capacitor forming a parallel LC circuit whose resonant frequency is a function of IOP.
Most parts of the sensor sit externally on the sclera and only the needle penetrates inside the vitreous space. In vitro tests show a sensitivity of 15 kHz/mmHg with approximately 1-mmHg resolution. One month in vivo implants in rabbits confirm biocompatibility and functionality of the device.
Furthermore, when IOP monitoring is complete, the design allows physicians to easily retrieve the transponder. The device consists of three main components: 1) a hypodermic needle (30 gauge) that penetrates the sclera through pars plana and establishes direct access to the vitreous space of the eye; 2) a micromachined capacitive pressure sensor connected to the needle back-end; and 3) a flexible polyimide coil connected to the capacitor forming a parallel LC circuit whose resonant frequency is a function of IOP.
Most parts of the sensor sit externally on the sclera and only the needle penetrates inside the vitreous space. In vitro tests show a sensitivity of 15 kHz/mmHg with approximately 1-mmHg resolution. One month in vivo implants in rabbits confirm biocompatibility and functionality of the device.
A Model for the Optimization of the Maintenance Support Organization for Offshore Wind Farms
Maintenance of offshore wind power plants is known to be extensive and costly. This paper presents a model for optimizing the maintenance support organization of an offshore wind farm: the location of maintenance accommodation, the number of technicians, the choice of transfer vessels, and the use of a helicopter.
The model includes an analysis of a transportation strategy using alternative transportation means, a queuing model of maintenance activities, and an economic model of the maintenance support organization. An example based on a generic 100 wind turbine 5-MW wind farm is used to demonstrate the application of the model.
The results show the benefit of the production losses of the different options, which enables the identification of an optimal maintenance support organization based on the reliability, logistic costs, and electricity price. The most cost-efficient maintenance support organization in the case study consists of an offshore accommodation with technicians on service 24 hours a day, 7 days a week.
The solution suggests transportation by use of a crew transfer vessel equipped with a motion compensated access system.
The model includes an analysis of a transportation strategy using alternative transportation means, a queuing model of maintenance activities, and an economic model of the maintenance support organization. An example based on a generic 100 wind turbine 5-MW wind farm is used to demonstrate the application of the model.
The results show the benefit of the production losses of the different options, which enables the identification of an optimal maintenance support organization based on the reliability, logistic costs, and electricity price. The most cost-efficient maintenance support organization in the case study consists of an offshore accommodation with technicians on service 24 hours a day, 7 days a week.
The solution suggests transportation by use of a crew transfer vessel equipped with a motion compensated access system.
A Modeling Approach to Analyze Variability of Remanufacturing Process Routing
Remanufacturing is a practice of growing importance due to increasing environmental awareness and regulations. However, little research focuses on stochastic remanufacturing process routings (RPR).
This paper presents an analytical method, where four Graphical Evaluation and Review Technique (GERT)-based RPR models are proposed to mathematically represent and analyze the variability of remanufacturing task sequences. In particular, with the method, the probability of individual processes being taken in a remanufacturing system and the time associated with them can be efficiently determined.
The proposed method is demonstrated through the remanufacturing of used lathe spindles and telephones, and verified by Arena simulation. Numerical experiments that investigate the relationships between RPR dynamics and other system parameters (such as inventory control for due-time performance and time buffer sA Network Flow Model for the Performance Evaluation and Design of Material Separation Systems for Recyclingize for bottleneck control) are included.
This paper presents an analytical method, where four Graphical Evaluation and Review Technique (GERT)-based RPR models are proposed to mathematically represent and analyze the variability of remanufacturing task sequences. In particular, with the method, the probability of individual processes being taken in a remanufacturing system and the time associated with them can be efficiently determined.
The proposed method is demonstrated through the remanufacturing of used lathe spindles and telephones, and verified by Arena simulation. Numerical experiments that investigate the relationships between RPR dynamics and other system parameters (such as inventory control for due-time performance and time buffer sA Network Flow Model for the Performance Evaluation and Design of Material Separation Systems for Recyclingize for bottleneck control) are included.
A Network Flow Model for the Performance Evaluation and Design of Material Separation Systems for Recycling
Interest in recycling has surged due to increasing material costs, environmental concerns over material production and disposal, and laws designed to improve material recycling rates.
In response, recycling systems are becoming more complex as increasing material recovery is required from products with complicated material mixtures such as waste electrical and electronic equipment (WEEE) and ELVs. To increase performance and process complex material mixtures, separation systems are typically organized as highly integrated multistage systems.
However, the problem of estimating the performance and designing multistage separation systems has rarely been tackled from a systems engineering perspective, resulting in poor integration and suboptimal configuration of industrial multistage separation systems.
This paper presents a new approach to modeling, analyzing, and designing multistage separation systems to meet specified performance goals in terms of recovery/grade. Results can be used to generate maps of optimal system configurations for different requirements. The industrial benefits are illustrated bA New Type of Automatic Alarming Device to Rescue Accident Injured in Time y a real case study.
In response, recycling systems are becoming more complex as increasing material recovery is required from products with complicated material mixtures such as waste electrical and electronic equipment (WEEE) and ELVs. To increase performance and process complex material mixtures, separation systems are typically organized as highly integrated multistage systems.
However, the problem of estimating the performance and designing multistage separation systems has rarely been tackled from a systems engineering perspective, resulting in poor integration and suboptimal configuration of industrial multistage separation systems.
This paper presents a new approach to modeling, analyzing, and designing multistage separation systems to meet specified performance goals in terms of recovery/grade. Results can be used to generate maps of optimal system configurations for different requirements. The industrial benefits are illustrated bA New Type of Automatic Alarming Device to Rescue Accident Injured in Time y a real case study.
A New Type of Automatic Alarming Device to Rescue Accident Injured in Time
This paper puts forward a new type of automatic alarming device, and it has been applied in western China. This paper introduces the principle of the device, and puts forward the detection algorithm for detecting occurrence of an accident.
The device is suitable for different types of vehicles. We verify that the device can accurately detect an accident and judge crash types by testing whether the device may trigger false alarm when vehicle is during normal driving and sled test of vehicle frontal impact simulation.
The device is suitable for different types of vehicles. We verify that the device can accurately detect an accident and judge crash types by testing whether the device may trigger false alarm when vehicle is during normal driving and sled test of vehicle frontal impact simulation.
A Novel Approach for Broken Bar Fault Diagnosis in Induction Motors through Torque Monitoring
The cracked or broken bar fault constitutes about 5-10% of total induction motor failures and leads to malfunction as well as reduction of the motor's life cycle. This is the reason why there is continuous research on techniques for prompt detection.
In this study, a study of the influences of the broken bar fault to the electromagnetic characteristics of the induction motor is presented, using an asynchronous cage motor and finite element method analysis.
To this direction, two models have been created and studied: a healthy and one with a broken bar. Additionally, a new approach on the detection of the broken rotor bar fault through the electromagnetic torque monitoring is suggested and validated through experimental results. oncept of the green wave.
In this study, a study of the influences of the broken bar fault to the electromagnetic characteristics of the induction motor is presented, using an asynchronous cage motor and finite element method analysis.
To this direction, two models have been created and studied: a healthy and one with a broken bar. Additionally, a new approach on the detection of the broken rotor bar fault through the electromagnetic torque monitoring is suggested and validated through experimental results. oncept of the green wave.
A Novel designee of Electronic Voting system Using Finger Print
This manuscript presents details of a customized test system that enables carrying out broadbeam heavy ion SEE radiation testing of semiconductor devices at cryogenic temperatures, while the device is biased and operational, and its application to measure the temperature dependence of single event transients in a CMOS circuit.
The cryogenic test system is lightweight and portable, and allows use of either liquid nitrogen (LN2, boiling point -196°C) or liquid helium (LHe, boiling point -269°C). The semiconductor device under test (DUT) can be tested either as a bare die affixed to a custom cold finger or as part of a printed circuit board (PCB) circuit
The cryogenic test system is lightweight and portable, and allows use of either liquid nitrogen (LN2, boiling point -196°C) or liquid helium (LHe, boiling point -269°C). The semiconductor device under test (DUT) can be tested either as a bare die affixed to a custom cold finger or as part of a printed circuit board (PCB) circuit
A Pervasive Health System Integrating Patient Monitoring, Status Logging, and Social Sharing
In this paper, we present the design and development of a pervasive health system enabling self-management of chronic patients during their everyday activities. The proposed system integrates patient health monitoring, status logging for capturing various problems or symptoms met, and social sharing of the recorded information within the patient's community, aiming to facilitate disease management.
A prototype is implemented on a mobile device illustrating the feasibility and applicability of the presented work by adopting unobtrusive vital signs monitoring through a wearable multisensing device, a service-oriented architecture for handling communication issues, and popular microblogging services.
Furthermore, a study has been conducted with 16 hypertensive patients, in order to investigate the user acceptance, the usefulness, and the virtue of the proposed system. The results show that the system is welcome by the chronic patients who are especially willing to share healthcare information, and is easy to learn and use, while its features have been overall regarded by the patients as helpful for their disease management and treatment.
A prototype is implemented on a mobile device illustrating the feasibility and applicability of the presented work by adopting unobtrusive vital signs monitoring through a wearable multisensing device, a service-oriented architecture for handling communication issues, and popular microblogging services.
Furthermore, a study has been conducted with 16 hypertensive patients, in order to investigate the user acceptance, the usefulness, and the virtue of the proposed system. The results show that the system is welcome by the chronic patients who are especially willing to share healthcare information, and is easy to learn and use, while its features have been overall regarded by the patients as helpful for their disease management and treatment.
A Petri Net and Extended Genetic Algorithm Combined Scheduling Method for Wafer Fabrication
As one of the most complicated manufacturing processes, semiconductor manufacturing consists of four steps, wafer sort, wafer fabrication, assembly, and testing. Among them, wafer fabrication is the most costly, complex, and time consuming step. Its operation management and optimization are challenging modeling and scheduling researchers.
To address its modeling issue, a hierarchical colored timed Petri net (HCTPN) is proposed, which can be used to describe various states, behavior and substructures of a wafer fabrication system. To address its scheduling issue, intelligent algorithms are introduced to the proposed HCTPN.
An extended genetic algorithm (EGA) embedded scheduling strategy over HCTPN is studied to optimize the combination of scheduling policies. The combined approach can conduct more efficient search with better scheduling performance. At last, a real case is presented to illustrate the results. Based on comparing simulation results of different scheduling strategies, the HCTPN and EGA combined scheduling is proved to be valid and efficient.
To address its modeling issue, a hierarchical colored timed Petri net (HCTPN) is proposed, which can be used to describe various states, behavior and substructures of a wafer fabrication system. To address its scheduling issue, intelligent algorithms are introduced to the proposed HCTPN.
An extended genetic algorithm (EGA) embedded scheduling strategy over HCTPN is studied to optimize the combination of scheduling policies. The combined approach can conduct more efficient search with better scheduling performance. At last, a real case is presented to illustrate the results. Based on comparing simulation results of different scheduling strategies, the HCTPN and EGA combined scheduling is proved to be valid and efficient.
A Probabilistic Framework for Decision-Making in Collision Avoidance Systems
This paper is concerned with the problem of decision-making in systems that assist drivers in avoiding collisions. An important aspect of these systems is not only assisting the driver when needed but also not disturbing the driver with unnecessary interventions.
Aimed at improving both of these properties, a probabilistic framework is presented for jointly evaluating the driver acceptance of an intervention and the necessity thereof to automatically avoid a collision. The intervention acceptance is modeled as high if it estimated that the driver judges the situation as critical, based on the driver's observations and predictions of the traffic situation.
One advantage with the proposed framework is that interventions can be initiated at an earlier stage when the estimated driver acceptance is high. Using a simplified driver model, the framework is applied to a few different types of collision scenarios.
The results show that the framework has appealing properties, both with respect to increasing the system benefit and to decreasi A Reliable Transmission Protocol for Zigbee – Based Wireless Patient Monitoringng the risk of unnecessary interventions.
Aimed at improving both of these properties, a probabilistic framework is presented for jointly evaluating the driver acceptance of an intervention and the necessity thereof to automatically avoid a collision. The intervention acceptance is modeled as high if it estimated that the driver judges the situation as critical, based on the driver's observations and predictions of the traffic situation.
One advantage with the proposed framework is that interventions can be initiated at an earlier stage when the estimated driver acceptance is high. Using a simplified driver model, the framework is applied to a few different types of collision scenarios.
The results show that the framework has appealing properties, both with respect to increasing the system benefit and to decreasi A Reliable Transmission Protocol for Zigbee – Based Wireless Patient Monitoringng the risk of unnecessary interventions.
A Reliable Transmission Protocol for Zigbee – Based Wireless Patient Monitoring
Patient monitoring systems are gaining their importance as the fast-growing global elderly population increases demands for caretaking. These systems use wireless technologies to transmit vital signs for medical evaluation. In a multihop ZigBee network, the existing systems usually use broadcast or multicast schemes to increase the reliability of signals transmission; however, both the schemes lead to significantly higher network traffic and end-to-end transmission delay.
In this paper, we present a reliable transmission protocol based on anycast routing for wireless patient monitoring. Our scheme automatically selects the closest data receiver in an anycast group as a destination to reduce the transmission latency as well as the control overhead.
The new protocol also shortens the latency of path recovery by initiating route recovery from the intermediate routers of the original path. On the basis of a reliable transmission scheme, we implement a ZigBee device for fall monitoring, which integrates fall detection, indoor positioning, and ECG monitoring. When the triaxial accelerometer of the device detects a fall, the current position of the patient is transmitted to an emergency center through a ZigBee network.
In order to clarify the situation of the fallen patient, 4-s ECG signals are also transmitted. Our transmission scheme ensures the successful transmission of these critical messages. The experimental results show that our scheme is fast and reliable. We also demonstrate that our devices can seamlessly integrate with the next generation technology of wireless wide area network, worldwide interoperability for microwave access, to achieve real-time patient monitoring.
In this paper, we present a reliable transmission protocol based on anycast routing for wireless patient monitoring. Our scheme automatically selects the closest data receiver in an anycast group as a destination to reduce the transmission latency as well as the control overhead.
The new protocol also shortens the latency of path recovery by initiating route recovery from the intermediate routers of the original path. On the basis of a reliable transmission scheme, we implement a ZigBee device for fall monitoring, which integrates fall detection, indoor positioning, and ECG monitoring. When the triaxial accelerometer of the device detects a fall, the current position of the patient is transmitted to an emergency center through a ZigBee network.
In order to clarify the situation of the fallen patient, 4-s ECG signals are also transmitted. Our transmission scheme ensures the successful transmission of these critical messages. The experimental results show that our scheme is fast and reliable. We also demonstrate that our devices can seamlessly integrate with the next generation technology of wireless wide area network, worldwide interoperability for microwave access, to achieve real-time patient monitoring.
A Robot that Approaches Pedestrians
When robots serve in urban areas such as shopping malls, they will often be required to approach people in order to initiate service. This paper presents a technique for human-robot interaction that enables a robot to approach people who are passing through an environment.
For successful approach, our proposed planner first searches for a target person at public distance zones anticipating his/her future position and behavior. It chooses a person who does not seem busy and can be reached from a frontal direction. Once the robot successfully approaches the person within the social distance zone, it identifies the person's reaction and provides a timely response by coordinating its body orientation.
The system was tested in a shopping mall and compared with a simple approaching method. The result demonstrates a significant improvement in approaching performance; the simple method was only 35.1% successful, whereas the proposed technique showed a success rate of 55.9%.
For successful approach, our proposed planner first searches for a target person at public distance zones anticipating his/her future position and behavior. It chooses a person who does not seem busy and can be reached from a frontal direction. Once the robot successfully approaches the person within the social distance zone, it identifies the person's reaction and provides a timely response by coordinating its body orientation.
The system was tested in a shopping mall and compared with a simple approaching method. The result demonstrates a significant improvement in approaching performance; the simple method was only 35.1% successful, whereas the proposed technique showed a success rate of 55.9%.
A Robust Wearable health monitoring system based On WSN
Health monitoring system is one of most important and practical applications of wireless sensor network (WSN). Even though various health monitoring devices based on WSN are used, they are still quite limited in the sense of mobility and accuracy.
In this paper a new wearable health monitoring system is proposed, which consists of bio-shirt and vital sensor node. Here the accuracy of the measurement of electrocardiogram signal is enhanced, and the sensor node is optimized for the use in WSN. Also, a multi-hop routing protocol is employed to effectively deal with rapid changes in the link between a fast moving target node and static relay nodes.
The experiments for various types of movements of an individual wearing the proposed bio-shirt reveal that the proposed system significantly improves the performance of health monitoring based on WSN compared to the existing device.
In this paper a new wearable health monitoring system is proposed, which consists of bio-shirt and vital sensor node. Here the accuracy of the measurement of electrocardiogram signal is enhanced, and the sensor node is optimized for the use in WSN. Also, a multi-hop routing protocol is employed to effectively deal with rapid changes in the link between a fast moving target node and static relay nodes.
The experiments for various types of movements of an individual wearing the proposed bio-shirt reveal that the proposed system significantly improves the performance of health monitoring based on WSN compared to the existing device.
A Semi-Automated Positioning System for Contact-Mode Atomic Force Microscopy (AFM)
Contact mode Atomic Force Microscopy (CM-AFM) is popularly used by the biophysics community to study mechanical properties of cells cultured in petri dishes, or tissue sections fixed on microscope slides. While cells are fairly easy to locate, sampling in spatially heterogeneous tissue specimens is laborious and time-consuming at higher magnifications.
Furthermore, tissue registration across multiple magnifications for AFM-based experiments is a challenging problem, suggesting the need to automate the process of AFM indentation on tissue.
In this work, we have developed an image-guided micropositioning system to align the AFM probe and human breast-tissue cores in an automated manner across multiple magnifications. Our setup improves efficiency of the AFM indentation experiments considerably.
Furthermore, tissue registration across multiple magnifications for AFM-based experiments is a challenging problem, suggesting the need to automate the process of AFM indentation on tissue.
In this work, we have developed an image-guided micropositioning system to align the AFM probe and human breast-tissue cores in an automated manner across multiple magnifications. Our setup improves efficiency of the AFM indentation experiments considerably.
A sensor system for unsupervised residential power usage monitoring
As a key technology of home area networks in smart grids, fine-grained power usage monitoring may help conserve electricity. Several existing systems achieve this goal by exploiting appliances' power usage signatures identified in labor-intensive in situ training processes.
Recent work shows that autonomous power usage monitoring can be achieved by supplementing a smart meter with distributed sensors that detect the working states of appliances. However, sensors must be carefully installed for each appliance, resulting in high installation cost.
This paper presents Supero - the first ad hoc sensor system that can monitor appliance power usage without supervised training. By exploiting multisensor fusion and unsupervised machine learning algorithms, Supero can classify the appliance events of interest and autonomously associate measured power usage with the respective appliances.
Our extensive evaluation in five real homes shows that Supero can estimate the energy consumption with errors less than 7.5%. Moreover, non-professional users can quickly deploy Supero with considerable flexibility.
Recent work shows that autonomous power usage monitoring can be achieved by supplementing a smart meter with distributed sensors that detect the working states of appliances. However, sensors must be carefully installed for each appliance, resulting in high installation cost.
This paper presents Supero - the first ad hoc sensor system that can monitor appliance power usage without supervised training. By exploiting multisensor fusion and unsupervised machine learning algorithms, Supero can classify the appliance events of interest and autonomously associate measured power usage with the respective appliances.
Our extensive evaluation in five real homes shows that Supero can estimate the energy consumption with errors less than 7.5%. Moreover, non-professional users can quickly deploy Supero with considerable flexibility.
A Simulation-Based Tool for Energy Efficient Building Design for a Class of Manufacturing Plants
This paper explores energy efficient building design for manufacturing plants. Many efforts have been directed into the field of building design optimization concerning building energy performance, but most of the studies focus on residential buildings or public buildings.
Very limited research results studying plants buildings have been reported. However, plants buildings have certain unique features that make the design problem more challenging. Furthermore, the approaches presented in the current publications could not guarantee the performance of their designs if the computation capacity is limited. This paper attempts to address these two issues.
First, an EnergyPlus-integrated overall energy consumption estimation framework is developed for a class of manufacturing plants, where the environmental conditions would not affect the energy consumption of the production processes. Based on that, the building design problem for this type of manufacturing plants is formulated as a stochastic programming problem concerning uncertainties arising from the future weather conditions and energy prices, where seasonal production scheduling optimizing is incorporated when estimating the performance of building designs.
Second, Ordinal Optimization (OO) method is introduced to solve the problem so as to quantitatively guarantee a high probability of finding satisfactory designs while reducing the computation burden. A numerical example is provided, showing our solution method performs effectively in finding a satisfactory design.
Very limited research results studying plants buildings have been reported. However, plants buildings have certain unique features that make the design problem more challenging. Furthermore, the approaches presented in the current publications could not guarantee the performance of their designs if the computation capacity is limited. This paper attempts to address these two issues.
First, an EnergyPlus-integrated overall energy consumption estimation framework is developed for a class of manufacturing plants, where the environmental conditions would not affect the energy consumption of the production processes. Based on that, the building design problem for this type of manufacturing plants is formulated as a stochastic programming problem concerning uncertainties arising from the future weather conditions and energy prices, where seasonal production scheduling optimizing is incorporated when estimating the performance of building designs.
Second, Ordinal Optimization (OO) method is introduced to solve the problem so as to quantitatively guarantee a high probability of finding satisfactory designs while reducing the computation burden. A numerical example is provided, showing our solution method performs effectively in finding a satisfactory design.
A Sub-Wavelength RF Source Tracking System for GPS-Denied Environments
A sub-wavelength source tracking system utilizing highly miniaturized antennas in the HF range for applications in GPS-denied environments including indoor and urban scenarios is proposed. A technique that combines a high resolution direction finding and radio triangulation utilizing a compact transmit (Tx) and receive (Rx) antenna system is pursued. Numerical models are used to investigate wave propagation and scattering in complex indoor scenarios as a function of frequency.
We choose HF band to minimize attenuation through walls and multipath in indoor environments. In order to achieve a compact system, a low-profile and highly miniaturized antenna ( ?/300 height and ?/100 lateral dimensions at 20 MHz) having omnidirectional, vertically polarized field is designed. At such low frequencies, accurate measurement of the phase difference between the signals at the Rx antennas having very small baseline is challenging.
To address this issue, a biomimetic circuit that mimics the hearing mechanism of a fly (Ormia Ochracea) is utilized. With this circuit, very small phase differences are amplified to measurable values. The numerical simulations are used to analyze direction of arrival retrieval and source localization in highly cluttered environments. A compact system prototype is also realized and source tracking in complex indoor scenarios is successfully demonstrated.
We choose HF band to minimize attenuation through walls and multipath in indoor environments. In order to achieve a compact system, a low-profile and highly miniaturized antenna ( ?/300 height and ?/100 lateral dimensions at 20 MHz) having omnidirectional, vertically polarized field is designed. At such low frequencies, accurate measurement of the phase difference between the signals at the Rx antennas having very small baseline is challenging.
To address this issue, a biomimetic circuit that mimics the hearing mechanism of a fly (Ormia Ochracea) is utilized. With this circuit, very small phase differences are amplified to measurable values. The numerical simulations are used to analyze direction of arrival retrieval and source localization in highly cluttered environments. A compact system prototype is also realized and source tracking in complex indoor scenarios is successfully demonstrated.
A System for Automatic Notification and Severity Estimation of Automotive Accidents
New communication technologies integrated into modern vehicles offer an opportunity for better assistance to people injured in traffic accidents. Recent studies show how communication capabilities should be supported by artificial intelligence systems capable of automating many of the decisions to be taken by emergency services, thereby adapting the rescue resources to the severity of the accident and reducing assistance time.
To improve the overall rescue process, a fast and accurate estimation of the severity of the accident represent a key point to help the emergency services to better estimate the required resources.
This paper proposes a novel intelligent system which is able to automatically detect road accidents, notify them through vehicular networks, and estimate their severity based on the concept of data mining and knowledge inference. Results show that a complete Knowledge Discovery in Databases (KDD) process, with an adequate selection of relevant features, allows generating estimation models able to predict the severity of new accidents.
We develop a prototype of our system based on off-the-shelf devices, and validate it at the Applus+ IDIADA Automotive Research Corporation facilities, showing that our system can notably reduce the time needed to alert and deploy the emergency services after an accident takes place.
To improve the overall rescue process, a fast and accurate estimation of the severity of the accident represent a key point to help the emergency services to better estimate the required resources.
This paper proposes a novel intelligent system which is able to automatically detect road accidents, notify them through vehicular networks, and estimate their severity based on the concept of data mining and knowledge inference. Results show that a complete Knowledge Discovery in Databases (KDD) process, with an adequate selection of relevant features, allows generating estimation models able to predict the severity of new accidents.
We develop a prototype of our system based on off-the-shelf devices, and validate it at the Applus+ IDIADA Automotive Research Corporation facilities, showing that our system can notably reduce the time needed to alert and deploy the emergency services after an accident takes place.
A System-Prototype Representing 3D Space via Alternative-Sensing for Visually Impaired Navigation
Offering an alternative mode of interaction with the surrounding 3-D space to the visually impaired for collision free navigation is a goal of great significance that includes several key challenges.
In this paper, we study the alternative 3-D space sensation that is interpreted by our computer vision prototype system and transferred to the user via a vibration array. There are two main tasks for conducting such a study. The first task is to detect obstacles in close proximity, and motion patterns in image sequences, both important issues for a safe navigation in a 3-D dynamic space.
To achieve this task, the images from the left and right cameras are acquired to produce new stereo images, followed by video stabilization as a preprocessing stage, a nonlinear spatio-temporal diffusion and kernel based density estimation method to assess the motion activity, and finally watershed-based detection of moving regions (or obstacles) of interest. The second task is to efficiently represent the information of the captured static and dynamic visual scenes as 3-D detectable patterns of vibrations applied on the human body to create a 3-D sensation of the space during navigation.
To accomplish this task, considering the current limitations imposed by the technology, we create a high-to-low (H-L) image resolution representation scheme to facilitate the mapping onto a low-resolution 2-D array of vibrators. The H-L scheme uses pyramidal modeling to obtain low-resolution images of interest-preserving motion and obstacles-that are mapped onto a vibration array.
These patterns are utilized to train and test the performance of the users in free space navigation. Thus, in this paper we study the synergy of these two important schemes to offer an alternative sensation of the 3-D space to the visually impaired via an array of vibrators.
Particularly, the motion component is employed as an element for the identification of visual information of interest to be retained during the H-L tran- formation. The role of the array vibrators is to create a small-scale front representation of the space via various levels of vibrations. Thus, 3-D vibrations applied on the user's body (chest, abdomen) offer a 3-D sensation of the surrounding space and the motion in it.
In addition, we present experimental results that indicate the efficiency of this navigation scheme in creating low-resolution 3-D views of the free navigation space and detecting obstacles and moving areas.
In this paper, we study the alternative 3-D space sensation that is interpreted by our computer vision prototype system and transferred to the user via a vibration array. There are two main tasks for conducting such a study. The first task is to detect obstacles in close proximity, and motion patterns in image sequences, both important issues for a safe navigation in a 3-D dynamic space.
To achieve this task, the images from the left and right cameras are acquired to produce new stereo images, followed by video stabilization as a preprocessing stage, a nonlinear spatio-temporal diffusion and kernel based density estimation method to assess the motion activity, and finally watershed-based detection of moving regions (or obstacles) of interest. The second task is to efficiently represent the information of the captured static and dynamic visual scenes as 3-D detectable patterns of vibrations applied on the human body to create a 3-D sensation of the space during navigation.
To accomplish this task, considering the current limitations imposed by the technology, we create a high-to-low (H-L) image resolution representation scheme to facilitate the mapping onto a low-resolution 2-D array of vibrators. The H-L scheme uses pyramidal modeling to obtain low-resolution images of interest-preserving motion and obstacles-that are mapped onto a vibration array.
These patterns are utilized to train and test the performance of the users in free space navigation. Thus, in this paper we study the synergy of these two important schemes to offer an alternative sensation of the 3-D space to the visually impaired via an array of vibrators.
Particularly, the motion component is employed as an element for the identification of visual information of interest to be retained during the H-L tran- formation. The role of the array vibrators is to create a small-scale front representation of the space via various levels of vibrations. Thus, 3-D vibrations applied on the user's body (chest, abdomen) offer a 3-D sensation of the surrounding space and the motion in it.
In addition, we present experimental results that indicate the efficiency of this navigation scheme in creating low-resolution 3-D views of the free navigation space and detecting obstacles and moving areas.
A Tactical Information Management System for Unmanned Vehicles Using Vehicular Ad-hoc Network
Unmanned Ground Vehicles (UGV) are playing a vital role in Military Services. The main abstract of this project is proposed for provide a Tactical information Management system for Unmanned Ground Vehicles using Vehicular Ad-hoc Networks (VANET). VANET is a perfect option for vehicle to vehicle communication to share the Information with each other.
An Information Control Unit will be attached in-built with all unmanned ground vehicles to share the information. An Information Control unit consists of front and rear Radar (Radio Detection and Ranging), Event Data Recorder, Global positioning system (GPS), Sensor, and a communication system.
When a failure detected in an Unmanned Ground vehicle due to the enemy attack, the tactical information will be shared with the neighboured UGVs among the VANET about the status of failed UGV.
The damaged UGV will be replaced immediately with the neighbour to fill up the gap using the Tactical information shared using the WAVE (Wireless Application for Vehicle Environment) SMS protocol. This information is used to avoid collision also during fog.
An Information Control Unit will be attached in-built with all unmanned ground vehicles to share the information. An Information Control unit consists of front and rear Radar (Radio Detection and Ranging), Event Data Recorder, Global positioning system (GPS), Sensor, and a communication system.
When a failure detected in an Unmanned Ground vehicle due to the enemy attack, the tactical information will be shared with the neighboured UGVs among the VANET about the status of failed UGV.
The damaged UGV will be replaced immediately with the neighbour to fill up the gap using the Tactical information shared using the WAVE (Wireless Application for Vehicle Environment) SMS protocol. This information is used to avoid collision also during fog.
A tactile micro transceiver for finger tip touch and movement recognition with texture expression
We present a tactile information transceiver for fingertip touch and movement recognition with the texture expression functions, using a friction-tunable capacitive slider-pad. Compared to the conventional tactile devices focused on tactile input function, the present device integrates the tactile input function and the tactile output function of texture expression.
The tactile transceiver, composed of the top slider-layer and the bottom electrode layer, recognizes z-axis fingertip touch as well as x-/y-axis lateral movements from the capacitance change between top and the bottom layers.
The electrostatic attraction force between the two layers modifies interlayer friction force; thus expressing texture to fingertip. In the experiment, the tactile transceiver recognizes both vertical touch and lateral movements of fingertip with the detection sensitivity of 0.146±0.02nF/40µm and 0.03±0.02nF/250µm, respectively. The texture has been expressed to the fingertip by the varying friction force in the range of 121~580mN.
The tactile transceiver, composed of the top slider-layer and the bottom electrode layer, recognizes z-axis fingertip touch as well as x-/y-axis lateral movements from the capacitance change between top and the bottom layers.
The electrostatic attraction force between the two layers modifies interlayer friction force; thus expressing texture to fingertip. In the experiment, the tactile transceiver recognizes both vertical touch and lateral movements of fingertip with the detection sensitivity of 0.146±0.02nF/40µm and 0.03±0.02nF/250µm, respectively. The texture has been expressed to the fingertip by the varying friction force in the range of 121~580mN.
A Topology based Model for Railway Train Control Systems
An innovative topology-based method for modeling railway train control systems is proposed in this paper. The method addresses the problems of having to rely too much on designers' experience and of incurring excessive cost of validation and verification in the development of railway train control systems.
Four topics are discussed in the paper: 1) the definition of basic topological units for modeling railway networks, based on the essential characteristics of these units; 2) the concept of a train movement authority topological space; 3) the interpretation of the train control logic as a topological space construct; and 4) topological space theorems for train control system verification.
A case study is also presented, where the approach was applied in the simulation model of a typical railway network, and the results show good performance, which meets the system requirements.
Four topics are discussed in the paper: 1) the definition of basic topological units for modeling railway networks, based on the essential characteristics of these units; 2) the concept of a train movement authority topological space; 3) the interpretation of the train control logic as a topological space construct; and 4) topological space theorems for train control system verification.
A case study is also presented, where the approach was applied in the simulation model of a typical railway network, and the results show good performance, which meets the system requirements.
A UAV system for inspection of industrial facilities
This work presents a small-scale Unmanned Aerial System (UAS) capable of performing inspection tasks in enclosed industrial environments. Vehicles with such capabilities have the potential to reduce human involvement in hazardous tasks and can minimize facility outage periods.
The results presented generalize to UAS exploration tasks in almost any GPS-denied indoor environment. The contribution of this work is twofold. First, results from autonomous flights inside an industrial boiler of a power plant are presented. A lightweight, vision-aided inertial navigation system provides reliable state estimates under difficult environmental conditions typical for such sites. It relies solely on measurements from an on-board MEMS inertial measurement unit and a pair of cameras arranged in a classical stereo configuration.
A model-predictive controller allows for efficient trajectory following and enables flight in close proximity to the boiler surface. As a second contribution, we highlight ongoing developments by displaying state estimation and structure recovery results acquired with an integrated visual/inertial sensor that will be employed on future aerial service robotic platforms. A tight integration in hardware facilitates spatial and temporal calibration of the different sensors and thus enables more accurate and robust ego-motion estimates.
Comparison with ground truth obtained from a laser tracker shows that such a sensor can provide motion estimates with drift rates of only few centimeters over the period of a typical flight.
The results presented generalize to UAS exploration tasks in almost any GPS-denied indoor environment. The contribution of this work is twofold. First, results from autonomous flights inside an industrial boiler of a power plant are presented. A lightweight, vision-aided inertial navigation system provides reliable state estimates under difficult environmental conditions typical for such sites. It relies solely on measurements from an on-board MEMS inertial measurement unit and a pair of cameras arranged in a classical stereo configuration.
A model-predictive controller allows for efficient trajectory following and enables flight in close proximity to the boiler surface. As a second contribution, we highlight ongoing developments by displaying state estimation and structure recovery results acquired with an integrated visual/inertial sensor that will be employed on future aerial service robotic platforms. A tight integration in hardware facilitates spatial and temporal calibration of the different sensors and thus enables more accurate and robust ego-motion estimates.
Comparison with ground truth obtained from a laser tracker shows that such a sensor can provide motion estimates with drift rates of only few centimeters over the period of a typical flight.
A User Customizable Urban Traffic Information Collection Method based on Wireless Sensor Networks
Traffic monitoring can efficiently promote urban planning and encourage better use of public transport. Efficient traffic information collection is one important part of traffic monitoring systems. Based on a technique using wireless sensor networks (WSNs), this paper provides a flexible framework for regional traffic information collection in accordance with user request.
This framework serves as a basis for future research in designing and implementing traffic monitoring applications. A two-layer network architecture is established for traffic information acquisition in the context of a WSN environment. In addition, a user-customizable data-centric routing scheme is proposed for traffic information delivery, in which multiple routing-related information is considered for decision-making to meet different user requirements.
Simulations have shown good performance of the proposed routing scheme compared with other traditional routing schemes on a real-world urban traffic network.
This framework serves as a basis for future research in designing and implementing traffic monitoring applications. A two-layer network architecture is established for traffic information acquisition in the context of a WSN environment. In addition, a user-customizable data-centric routing scheme is proposed for traffic information delivery, in which multiple routing-related information is considered for decision-making to meet different user requirements.
Simulations have shown good performance of the proposed routing scheme compared with other traditional routing schemes on a real-world urban traffic network.
A Wi-Fi based smart wireless sensor network for monitoring an Agricultural Environment
The main objective of the present work is to develop a smart wireless sensor network (WSN) for an agricultural environment. Monitoring of environmental factors have increased in importance over the last decade. In particular monitoring agricultural environments for various factors such as temperature and humidity along with other factors can be of significance.
A traditional approach to measuring these factors in an agricultural environment meant individuals manually taking measurements and checking them at various times. The ability to document and detail changes in parameters of interest have become increasingly valuable, to such an extent that unattended monitoring systems have been investigated for this function.
This study investigates a remote monitoring system using WiFi, where the wireless sensor nodes are based on WSN802G modules. These nodes send data wirelessly to a central server, which collects the data, stores it and will allow it to be analyzed then displayed as needed.
A traditional approach to measuring these factors in an agricultural environment meant individuals manually taking measurements and checking them at various times. The ability to document and detail changes in parameters of interest have become increasingly valuable, to such an extent that unattended monitoring systems have been investigated for this function.
This study investigates a remote monitoring system using WiFi, where the wireless sensor nodes are based on WSN802G modules. These nodes send data wirelessly to a central server, which collects the data, stores it and will allow it to be analyzed then displayed as needed.
A Wireless Electrocardiogram Detection for Personal Health Monitoring
The current paper presents low-power analog integrated circuits (ICs) for wireless electrocardiogram (ECG) detection in personal health monitoring. Considering the power-efficient communication in the body sensor network (BSN), the required low-power analog ICs are developed for a healthcare system through miniaturization and system integration.
The proposed system comprises the design and implementation with three subsystems, namely, (1) the ECG acquisition node, (2) the protocol for standard IEEE 802.15.4 ZigBee system, and (3) the radio frequency (RF) transmitter circuits. A preamplifier, a low-pass filter, and a successive-approximation analog-to-digital converter (SA-ADC) are integrated to detect an ECG signal. For high integration, the ZigBee protocol is adopted for wireless communication.
To transmit the ECG signal through wireless communication, a quadrature voltage-controlled oscillator and a 2.4 GHz low-IF transmitter with a power amplifier and up-conversion mixer are also developed. In the receiver, a 2.4 GHz fully integrated CMOS radio-frequency front-end with a low-noise amplifier, and a quadrature mixer is proposed.
The low-power wireless bio-signal acquisition SoC (WBSA-SoC) has been implemented in TSMC 0.18-µm standard CMOS process. The measurement results on the human body reveal that the ECG signals can be acquired effectively by the proposed SoC.
The proposed system comprises the design and implementation with three subsystems, namely, (1) the ECG acquisition node, (2) the protocol for standard IEEE 802.15.4 ZigBee system, and (3) the radio frequency (RF) transmitter circuits. A preamplifier, a low-pass filter, and a successive-approximation analog-to-digital converter (SA-ADC) are integrated to detect an ECG signal. For high integration, the ZigBee protocol is adopted for wireless communication.
To transmit the ECG signal through wireless communication, a quadrature voltage-controlled oscillator and a 2.4 GHz low-IF transmitter with a power amplifier and up-conversion mixer are also developed. In the receiver, a 2.4 GHz fully integrated CMOS radio-frequency front-end with a low-noise amplifier, and a quadrature mixer is proposed.
The low-power wireless bio-signal acquisition SoC (WBSA-SoC) has been implemented in TSMC 0.18-µm standard CMOS process. The measurement results on the human body reveal that the ECG signals can be acquired effectively by the proposed SoC.
A Wireless Passive Sensor for Temperature Compensated Remote PH Monitoring
Temperature must be accounted for in order to provide accurate measurements in electrode-based pH sensors. We present an integrated wireless passive sensor for remote pH monitoring employing temperature compensation.
The sensor is a resonant circuit consisting of a planar spiral inductor connected in parallel to a temperature-dependent resistor (thermistor) and a voltage-dependent capacitor (varactor). A pH combination electrode consisting of an iridium/iridium oxide sensing electrode and a silver/silver chloride reference electrode, is connected in parallel with the varactor. A potential difference change across the electrodes due to pH variation of the solution changes the voltage-dependent capacitance and shifts the resonant frequency, while temperature of the solution affects the resistance and changes the quality factor of the sensor.
An interrogator coil is inductively coupled to the sensor inductor and remotely tracks the resonant frequency and quality factor of the sensor. The sensor is calibrated for temperature over a range of 25°C -55°C and pH over a 1.5-12 dynamic range. By employing temperature compensation, a measurement accuracy of less than 0.1 pH is achieved and the response time of the sensor is demonstrated to be less than 1 s.
The sensor overcomes the pH measurement error due to the temperature dependence of electrode-based passive pH sensors and has applications in remote pH monitoring where temperature varies over a wide range.
The sensor is a resonant circuit consisting of a planar spiral inductor connected in parallel to a temperature-dependent resistor (thermistor) and a voltage-dependent capacitor (varactor). A pH combination electrode consisting of an iridium/iridium oxide sensing electrode and a silver/silver chloride reference electrode, is connected in parallel with the varactor. A potential difference change across the electrodes due to pH variation of the solution changes the voltage-dependent capacitance and shifts the resonant frequency, while temperature of the solution affects the resistance and changes the quality factor of the sensor.
An interrogator coil is inductively coupled to the sensor inductor and remotely tracks the resonant frequency and quality factor of the sensor. The sensor is calibrated for temperature over a range of 25°C -55°C and pH over a 1.5-12 dynamic range. By employing temperature compensation, a measurement accuracy of less than 0.1 pH is achieved and the response time of the sensor is demonstrated to be less than 1 s.
The sensor overcomes the pH measurement error due to the temperature dependence of electrode-based passive pH sensors and has applications in remote pH monitoring where temperature varies over a wide range.
A wireless Smart Sensor Network Based on Multifunction Inter aerometric Radar Sensors for structural Health Monitoring
Structural health monitoring calls for sensors that are low-cost, low-profile, and power-constraint. It also requires the sensors to form a network to accurately monitor the low-frequency response that often occurs in many civil structures such as long-span bridges. However, the existing sensors are either not practical for wireless implementation, does not have enough accuracy, or are not cost-effective.
This paper presents a multi-function interferometric radar sensor that can easily form a smart sensor network by the merit of the ZigBee mesh networking function integrated in the sensor. The radar sensor, integrated with a micro-controller, works in the arctangent-demodulated interferometric mode to monitor the structure's displacement with an accuracy of sub-millimeter.
Experimental results show that the smart sensor network using the multi-function radar sensors serves as a good alternative for monitoring structural health.
This paper presents a multi-function interferometric radar sensor that can easily form a smart sensor network by the merit of the ZigBee mesh networking function integrated in the sensor. The radar sensor, integrated with a micro-controller, works in the arctangent-demodulated interferometric mode to monitor the structure's displacement with an accuracy of sub-millimeter.
Experimental results show that the smart sensor network using the multi-function radar sensors serves as a good alternative for monitoring structural health.
A Zigbee SMS Alert System With Trust Mechanism In Wireless Sensor Networks
Wireless Sensor networks (WSN) are highly distributed networks of small, lightweight wireless nodes, deployed in large numbers to monitor the environment or system by measurement of physical parameters such as temperature, pressure or relative humidity. Building sensors has been made possible by the recent advances in micro - electro mechanical system (MEMS) technology.
In this paper we propose a novel architecture for alarm generation in wireless sensor zone with the use of trust mechanism. Trust between the sensor nodes is an important issue in wireless sensor network. Trust between the sensor nodes provides secure, reliable path for data packets and accurate alarm generation.
In this paper we propose a novel architecture for alarm generation in wireless sensor zone with the use of trust mechanism. Trust between the sensor nodes is an important issue in wireless sensor network. Trust between the sensor nodes provides secure, reliable path for data packets and accurate alarm generation.
Accelerometer based body sensing for Health Aging
Falls in elderly people have been recognized as a major health problem in aging population. This paper describes the development of an accurate, accelerometer based fall detector capable of locating the wearer and sending alarm short messages (SMS).
The device worn on the waist uses a two-stage fall detection algorithm, which senses rapid impact and body orientation of the wearer. To evaluate the device and the algorithm, an experiment on 5 subjects was conducted.
The device is especially adapted to safely and accurately monitor elderly people without influencing their privacy and comfort. It is hoped that such a device will promote an integrated approach to the management of falls of elderly in the community.
The device worn on the waist uses a two-stage fall detection algorithm, which senses rapid impact and body orientation of the wearer. To evaluate the device and the algorithm, an experiment on 5 subjects was conducted.
The device is especially adapted to safely and accurately monitor elderly people without influencing their privacy and comfort. It is hoped that such a device will promote an integrated approach to the management of falls of elderly in the community.
Accessible Display Design to Control Home Area Networks
Recently, the social inclusion and technical aid to assure autonomy to people with disabilities are getting attention all over the world. We present a display design for accessible interaction in home area networks.
Based on a research on the accessible interfaces state of the art, an interface design was proposed. This interface was implemented over a Tablet that controls the domestic devices through a home network controller prototype.
In order to evaluate the design, a research was conducted, interviewing people with disabilities in Brazil. This research consolidated a feasible accessible interface to control home area networks pointing out the main requirements for home area networks considering a diversified group of impairments.
Based on a research on the accessible interfaces state of the art, an interface design was proposed. This interface was implemented over a Tablet that controls the domestic devices through a home network controller prototype.
In order to evaluate the design, a research was conducted, interviewing people with disabilities in Brazil. This research consolidated a feasible accessible interface to control home area networks pointing out the main requirements for home area networks considering a diversified group of impairments.
Adaptive Dispatching Rule for Semiconductor Wafer Fabrication Facility
Uncertainty in semiconductor fabrication facilities (fabs) requires scheduling methods to attain quick real-time responses. They should be well tuned to track the changes of a production environment to obtain better operational performance. This paper presents an adaptive dispatching rule (ADR) whose parameters are determined dynamically by real-time information relevant to scheduling.
First, we introduce the workflow of ADR that considers both batch and non-batch processing machines to obtain improved fab-wide performance. It makes use of such information as due date of a job, workload of a machine, and occupation time of a job on a machine. Then, we use a backward propagation neural network (BPNN) and a particle swarm optimization (PSO) algorithm to find the relations between weighting parameters and real-time state information to adapt these parameters dynamically to the environment.
Finally, a real fab simulation model is used to demonstrate the proposed method. The simulation results show that ADR with constant weighting parameters outperforms the conventional dispatching rule on average; ADR with changing parameters tracking real-time production information over time is more robust than ADR with constant ones; and further improvements can be obtained by optimizing the weights and threshold values of BPNN with a PSO algorithm.
First, we introduce the workflow of ADR that considers both batch and non-batch processing machines to obtain improved fab-wide performance. It makes use of such information as due date of a job, workload of a machine, and occupation time of a job on a machine. Then, we use a backward propagation neural network (BPNN) and a particle swarm optimization (PSO) algorithm to find the relations between weighting parameters and real-time state information to adapt these parameters dynamically to the environment.
Finally, a real fab simulation model is used to demonstrate the proposed method. The simulation results show that ADR with constant weighting parameters outperforms the conventional dispatching rule on average; ADR with changing parameters tracking real-time production information over time is more robust than ADR with constant ones; and further improvements can be obtained by optimizing the weights and threshold values of BPNN with a PSO algorithm.
Adaptive PD Controller Modeled via Support Vector Regression for a Biped Robot
The real-time balance control of an eight link biped robot using a zero moment point (ZMP) dynamic model is difficult due to the processing time of the corresponding equations.
To overcome this limitation, an intelligent computing control technique is used. This technique is based on support vector regression (SVR). The method uses the ZMP error and its variation as inputs, and the output is the correction of the robot's torso necessary for its sagittal balance. The SVR is trained based on simulation data and their performance is verified with a real biped robot. The ZMP is calculated by reading four force sensors placed under each robot's foot.
The gait implemented in this biped is similar to a human gait that is acquired and adapted to the robot's size. Some experiments are presented, and the results show that the implemented gait combined with the SVR controller can be used to control this biped robot. The SVR controller performs the control in 0.2 ms.
To overcome this limitation, an intelligent computing control technique is used. This technique is based on support vector regression (SVR). The method uses the ZMP error and its variation as inputs, and the output is the correction of the robot's torso necessary for its sagittal balance. The SVR is trained based on simulation data and their performance is verified with a real biped robot. The ZMP is calculated by reading four force sensors placed under each robot's foot.
The gait implemented in this biped is similar to a human gait that is acquired and adapted to the robot's size. Some experiments are presented, and the results show that the implemented gait combined with the SVR controller can be used to control this biped robot. The SVR controller performs the control in 0.2 ms.
AFAM an Articulated Four Axes Micro robot for Nano scale Applications
Articulated Four Axes Microrobot (AFAM). Target application areas include micro and nano part manipulation and probing. The robot consists of a cantilever actuated along four axes: in-place X, Y and YAW ; out-of-plane pitch. The microrobot size spans a total volume of 3 mm × 1.5 × 1 mm (XYZ), and operates within a workspace envelope of 50 µm × 50 µm × 75 µm (XYZ).
This is by far the largest operating envelope of any micropositioner with nonplanar dexterity. As a result it can be classified as a new type of three-dimensional microrobot and a candidate for miniaturizing top-down assembly systems to dimensions under 1 cm3.
A key feature in this design is a cable-like microwire that transforms in-plane actuator displacement into out-of-plane pitch and yaw motion (via flexure joints). Finite-element analysis simulation followed by microfabrication and assembly processes developed to prototype the designs are described.
The microrobot is designed to carry an AFM tip as the end effector and accomplish nanoindentation on a polymer surface. The tip attachment technique and nanoindentation experiments have also been described in this paper.
Open loop precision has been characterized using a laser interferometer which measured an average resolution of 50 nm along XYZ, repeatability of 100 nm and accuracy of 500 nm. Experiments to determine microrobot reliability are also presented.
This is by far the largest operating envelope of any micropositioner with nonplanar dexterity. As a result it can be classified as a new type of three-dimensional microrobot and a candidate for miniaturizing top-down assembly systems to dimensions under 1 cm3.
A key feature in this design is a cable-like microwire that transforms in-plane actuator displacement into out-of-plane pitch and yaw motion (via flexure joints). Finite-element analysis simulation followed by microfabrication and assembly processes developed to prototype the designs are described.
The microrobot is designed to carry an AFM tip as the end effector and accomplish nanoindentation on a polymer surface. The tip attachment technique and nanoindentation experiments have also been described in this paper.
Open loop precision has been characterized using a laser interferometer which measured an average resolution of 50 nm along XYZ, repeatability of 100 nm and accuracy of 500 nm. Experiments to determine microrobot reliability are also presented.
AFM-Based Robotic Nano-Hand for Stable Manipulation at Nano-scale
One of the major limitations for Atomic Force Microscopy (AFM)-based nanomanipulation is that AFM only has one sharp tip as the end-effector, and can only apply a point force to the nanoobject, which makes it extremely difficult to achieve a stable manipulation.
For example, the AFM tip tends to slip-away during nanoparticle manipulation due to its small touch area, and there is no available strategy to manipulate a nanorod in a constant posture with a single tip since the applied point force can make the nanorod rotate more easily.
In this paper, a robotic nano-hand method is proposed to solve these problems. The basic idea is using a single tip to mimic the manipulation effect that multi-AFM tip can achieve through the planned high speed sequential tip pushing. The theoretical behavior models of nanoparticle and nanorod are developed, based on which the moving speed and trajectory of the AFM tip are planned artfully to form a nano-hand.
In this way, the slip-away problem during nanoparticle manipulation can be get rid of efficiently, and a posture constant manipulation for nanorod can be achieved. The simulation and experimental results demonstrate the effectiveness and advantages of the proposed method.
For example, the AFM tip tends to slip-away during nanoparticle manipulation due to its small touch area, and there is no available strategy to manipulate a nanorod in a constant posture with a single tip since the applied point force can make the nanorod rotate more easily.
In this paper, a robotic nano-hand method is proposed to solve these problems. The basic idea is using a single tip to mimic the manipulation effect that multi-AFM tip can achieve through the planned high speed sequential tip pushing. The theoretical behavior models of nanoparticle and nanorod are developed, based on which the moving speed and trajectory of the AFM tip are planned artfully to form a nano-hand.
In this way, the slip-away problem during nanoparticle manipulation can be get rid of efficiently, and a posture constant manipulation for nanorod can be achieved. The simulation and experimental results demonstrate the effectiveness and advantages of the proposed method.
Aided Navigation Techniques for Indoor And outdoor unmanned vehicles
This paper presents design considerations of indoor and outdoor navigation techniques proposed for unmanned vehicles (UV). In this paper, we mainly investigate the use and the advantages of wireless sensor networks (WSNs) for indoor navigation, and Global Positioning System (GPS) for outdoor navigation.
The system primarily uses laser range finder (LRF) measurements for indoor navigation, and is based on Extended Kalman Filter (EKF). For outdoor navigation the system uses Inertial Navigation System (INS) measurements. At periodical intervals the system integrates the measurements of an absolute sensor to improve estimations. The absolute sensor is a WSN interface for indoor navigation, and a GPS receiver for outdoor navigation.
Simulation studies were conducted using Unified System for Automation and Robot Simulation (USARSim) and Player/Stage. The results of USARSim based simulations prove the advantages of integrating GPS measurements. Player/Stage based simulations show the advantages of integrating Received Signal Strength Indicator (RSSI) measurements obtained from WSN interfaces.
In addition to the simulation studies, field tests with a custom-built Corobot autonomous robot platform will be realized to prove the effectiveness of the methods.
The system primarily uses laser range finder (LRF) measurements for indoor navigation, and is based on Extended Kalman Filter (EKF). For outdoor navigation the system uses Inertial Navigation System (INS) measurements. At periodical intervals the system integrates the measurements of an absolute sensor to improve estimations. The absolute sensor is a WSN interface for indoor navigation, and a GPS receiver for outdoor navigation.
Simulation studies were conducted using Unified System for Automation and Robot Simulation (USARSim) and Player/Stage. The results of USARSim based simulations prove the advantages of integrating GPS measurements. Player/Stage based simulations show the advantages of integrating Received Signal Strength Indicator (RSSI) measurements obtained from WSN interfaces.
In addition to the simulation studies, field tests with a custom-built Corobot autonomous robot platform will be realized to prove the effectiveness of the methods.
An Accelerometer-Based Digital Pen With a Trajectory Recognition Algorithm For Handwritten Digit and Gesture Recognition
This paper presents an accelerometer-based digital pen for handwritten digit and gesture trajectory recognition applications. The digital pen consists of a triaxial accelerometer, a microcontroller, and an RF wireless transmission module for sensing and collecting accelerations of handwriting and gesture trajectories.
The proposed trajectory recognition algorithm composes of the procedures of acceleration acquisition, signal preprocessing, feature generation, feature selection, and feature extraction. The algorithm is capable of translating time-series acceleration signals into important feature vectors. Users can use the pen to write digits or make hand gestures, and the accelerations of hand motions measured by the accelerometer are wirelessly transmitted to a computer for online trajectory recognition.
The algorithm first extracts the time- and frequency-domain features from the acceleration signals and, then, further identifies the most important features by a hybrid method: kernel-based class separability for selecting significant features and linear discriminant analysis for reducing the dimension of features.
The reduced features are sent to a trained probabilistic neural network for recognition. Our experimental results have successfully validated the effectiveness of the trajectory recognition algorithm for handwritten digit and gesture recognition using the proposed digital pen.
The proposed trajectory recognition algorithm composes of the procedures of acceleration acquisition, signal preprocessing, feature generation, feature selection, and feature extraction. The algorithm is capable of translating time-series acceleration signals into important feature vectors. Users can use the pen to write digits or make hand gestures, and the accelerations of hand motions measured by the accelerometer are wirelessly transmitted to a computer for online trajectory recognition.
The algorithm first extracts the time- and frequency-domain features from the acceleration signals and, then, further identifies the most important features by a hybrid method: kernel-based class separability for selecting significant features and linear discriminant analysis for reducing the dimension of features.
The reduced features are sent to a trained probabilistic neural network for recognition. Our experimental results have successfully validated the effectiveness of the trajectory recognition algorithm for handwritten digit and gesture recognition using the proposed digital pen.
An Accurate Instruction-Level Energy Estimation Model and Tool for Embedded Systems
Estimating the energy consumption of applications is a key aspect in optimizing embedded systems energy consumption. This paper proposes a simple yet accurate instruction-level energy estimation model for embedded systems. As a case study, the model parameters were determined for a commonly used ARM7TDMI-based microcontroller.
The total energy includes the energy consumption of the processor core, Flash memory, memory controller, and SRAM. The model parameters are instructions opcode, number of shift operations, register bank bit flips, instructions weight and their Hamming distance, and different types of memory accesses. Also, the effect of pipeline stalls have been considered.
In order to validate the proposed model, a physical hardware platform equipped with energy measurement capabilities was developed. We have conducted experiments on several embedded applications from MiBench benchmark suite and the results show less than 6% error in the energy consumption estimation.
We have also developed an energy profiler tool for the systems that use ARM7TDMI processors by embedding the model parameters in an instruction-level profiler from the SimpleScalar toolset which provides valuable information and guidelines for software energy optimization.
The total energy includes the energy consumption of the processor core, Flash memory, memory controller, and SRAM. The model parameters are instructions opcode, number of shift operations, register bank bit flips, instructions weight and their Hamming distance, and different types of memory accesses. Also, the effect of pipeline stalls have been considered.
In order to validate the proposed model, a physical hardware platform equipped with energy measurement capabilities was developed. We have conducted experiments on several embedded applications from MiBench benchmark suite and the results show less than 6% error in the energy consumption estimation.
We have also developed an energy profiler tool for the systems that use ARM7TDMI processors by embedding the model parameters in an instruction-level profiler from the SimpleScalar toolset which provides valuable information and guidelines for software energy optimization.
An Assembly-Skill-Transferring Method for Cellular Manufacturing System—Part I: Verification of the Proposed Method for Motor Skill
Although a cellular manufacturing system can produce diversified products flexibly, its assembly efficiency is mainly limited by the operators' assembly performance. To improve the operators' assembly performance without longtime training, an assembly-skill-transferring method was proposed to realize the assembly skill transfer process from skilled operators to novice operators.
In the cellular manufacturing system, the assembly skills consist of cognition skills and motor skills. Taking a “Peg-in-Hole Task” as an example, the effect of the proposed assembly transfer method was verified for motor skills. The results show that the proposed assembly-skill-transferring system can improve the novice operators' assembly performance greatly.
In the cellular manufacturing system, the assembly skills consist of cognition skills and motor skills. Taking a “Peg-in-Hole Task” as an example, the effect of the proposed assembly transfer method was verified for motor skills. The results show that the proposed assembly-skill-transferring system can improve the novice operators' assembly performance greatly.
An Effective Artificial Bee Colony Algorithm for a Real-World Hybrid Flow shop Problem in Steelmaking Process
This paper aims to provide a solution method for the real-world hybrid flowshop scheduling problem resulting from a steelmaking process, which has important applications in modern iron and steel industry.
We first present a mixed integer mathematic model based on a comprehensive investigation. Then, we develop a heuristic method and two improvement procedures for a given schedule based on the problem-specific characteristics. Finally, we propose an effective artificial bee colony (ABC) algorithm with the job-permutation-based representation for solving the scheduling problem.
The proposed ABC algorithm incorporates the heuristic and improvement procedures as well as new characteristics including a neighboring solution generation method and two enhanced strategies. To evaluate the proposed algorithm, we present several adaptations of other well-known and recent metaheuristics to the problem and conduct a serial of experiments with the instances generated according to real-world production process.
The results show that the proposed ABC algorithm is more effective than all other adaptations after comprehensive computational comparisons and statistical analysis.
We first present a mixed integer mathematic model based on a comprehensive investigation. Then, we develop a heuristic method and two improvement procedures for a given schedule based on the problem-specific characteristics. Finally, we propose an effective artificial bee colony (ABC) algorithm with the job-permutation-based representation for solving the scheduling problem.
The proposed ABC algorithm incorporates the heuristic and improvement procedures as well as new characteristics including a neighboring solution generation method and two enhanced strategies. To evaluate the proposed algorithm, we present several adaptations of other well-known and recent metaheuristics to the problem and conduct a serial of experiments with the instances generated according to real-world production process.
The results show that the proposed ABC algorithm is more effective than all other adaptations after comprehensive computational comparisons and statistical analysis.
An efficient SMS-based framework for public health surveillance
Public health surveillance is the ongoing systematic collection, analysis and interpretation of health-related data. It serves as an early warning system for impending public health emergencies. This paper presents an efficient framework for automated acquisition and storage of medical data using the infrastructure provided by Short Message Service (SMS).
The data to be collected are dynamically organized by constructing form components (text-field, date-field, pull-down menu, radio-button, check-box, etc.) which is designed by an administrator as well as privileged users at the field level. On demand, the form components can be downloaded from the server to the mobile devices in the form of SMS.
The SMS contains a structured EXtensible Markup Language (XML) specifying the layout of the form. After the medical data is acquired, an SMS containing the structured data is sent to the server which stores it into the database.
Finally, the server sends an acknowledgment SMS to the mobile on successful storage of the data. The proposed SMS based framework provides a low-bandwidth, reliable, efficient and cost effective solution for medical data acquisition as demonstrated by experimental results.
The data to be collected are dynamically organized by constructing form components (text-field, date-field, pull-down menu, radio-button, check-box, etc.) which is designed by an administrator as well as privileged users at the field level. On demand, the form components can be downloaded from the server to the mobile devices in the form of SMS.
The SMS contains a structured EXtensible Markup Language (XML) specifying the layout of the form. After the medical data is acquired, an SMS containing the structured data is sent to the server which stores it into the database.
Finally, the server sends an acknowledgment SMS to the mobile on successful storage of the data. The proposed SMS based framework provides a low-bandwidth, reliable, efficient and cost effective solution for medical data acquisition as demonstrated by experimental results.
An Embedded Systems Laboratory to Support Rapid Prototyping of Robotics and the Internet of Things
This paper describes a new approach for a course and laboratory designed to allow students to develop low-cost prototypes of robotic and other embedded devices that feature Internet connectivity, I/O, networking, a real-time operating system (RTOS), and object-oriented C/C++.
The application programming interface (API) libraries provided permit students to work at a higher level of abstraction. A low-cost 32-bit SOC RISC microcontroller module with flash memory, numerous I/O interfaces, and on-chip networking hardware is used to build prototypes. A cloud-based C/C++ compiler is used for software development. All student files are stored on a server, and any Web browser can be used for software development.
Breadboards are used in laboratory projects to rapidly build prototypes of robots and embedded devices using the microcontroller, networking, and other I/O subsystems on small breakout boards. The commercial breakout boards used provide a large assortment of modern sensors, drivers, display ICs, and external I/O connectors.
Resources provided include eBooks, laboratory assignments, and extensive Wiki pages with schematics and sample microcontroller application code for each breakout board.
The application programming interface (API) libraries provided permit students to work at a higher level of abstraction. A low-cost 32-bit SOC RISC microcontroller module with flash memory, numerous I/O interfaces, and on-chip networking hardware is used to build prototypes. A cloud-based C/C++ compiler is used for software development. All student files are stored on a server, and any Web browser can be used for software development.
Breadboards are used in laboratory projects to rapidly build prototypes of robots and embedded devices using the microcontroller, networking, and other I/O subsystems on small breakout boards. The commercial breakout boards used provide a large assortment of modern sensors, drivers, display ICs, and external I/O connectors.
Resources provided include eBooks, laboratory assignments, and extensive Wiki pages with schematics and sample microcontroller application code for each breakout board.
An Empirical Study of Communication Infrastructures Towards the Smart Grid: Design, Implementation, and Evaluation
The smart grid features ubiquitous interconnections of power equipments to enable two-way flows of electricity and information for various intelligent power management applications, such as accurate relay protection and timely demand response. To fulfill such pervasive equipment interconnects, a full-fledged communication infrastructure is of great importance in the smart grid.
There have been extensive works on disparate layouts of communication infrastructures in the smart grid by surveying feasible wired or wireless communication technologies, such as power line communications and cellular networks. Nevertheless, towards an operable, cost-efficient and backward-compatible communication solution, more comprehensive and practical understandings are still urgently needed regarding communication requirements, applicable protocols, and system performance.
Through such comprehensive understandings, we are prone to answer a fundamental question, how to design, implement and integrate communication infrastructures with power systems. In this paper, we address this issue in a case study of a smart grid demonstration project, the Future Renewable Electric Energy Delivery and Management (FREEDM) systems. By investigating communication scenarios, we first clarify communication requirements implied in FREEDM use cases. Then, we adopt a predominant protocol framework, Distributed Network Protocol 3.0 over TCP/IP (DNP3 over TCP/IP), to practically establish connections between electric devices for data exchanges in a small-scale FREEDM system setting, Green Hub.
Within the real-setting testbed, we measure the message delivery performance of the DNP3-based communication infrastructure. Our results reveal that diverse timing requirements of message deliveries are arguably primary concerns in a way that dominates viabilities of protocols or schemes in the communication infrastructure of the smart grid.
Accordingly, although DNP3 over TCP/IP is widely considered as a smart grid co- munication solution, it cannot satisfy communication requirements in some time-critical scenarios, such as relay protections, which claim a further optimization on the protocol efficiency of DNP3.
There have been extensive works on disparate layouts of communication infrastructures in the smart grid by surveying feasible wired or wireless communication technologies, such as power line communications and cellular networks. Nevertheless, towards an operable, cost-efficient and backward-compatible communication solution, more comprehensive and practical understandings are still urgently needed regarding communication requirements, applicable protocols, and system performance.
Through such comprehensive understandings, we are prone to answer a fundamental question, how to design, implement and integrate communication infrastructures with power systems. In this paper, we address this issue in a case study of a smart grid demonstration project, the Future Renewable Electric Energy Delivery and Management (FREEDM) systems. By investigating communication scenarios, we first clarify communication requirements implied in FREEDM use cases. Then, we adopt a predominant protocol framework, Distributed Network Protocol 3.0 over TCP/IP (DNP3 over TCP/IP), to practically establish connections between electric devices for data exchanges in a small-scale FREEDM system setting, Green Hub.
Within the real-setting testbed, we measure the message delivery performance of the DNP3-based communication infrastructure. Our results reveal that diverse timing requirements of message deliveries are arguably primary concerns in a way that dominates viabilities of protocols or schemes in the communication infrastructure of the smart grid.
Accordingly, although DNP3 over TCP/IP is widely considered as a smart grid co- munication solution, it cannot satisfy communication requirements in some time-critical scenarios, such as relay protections, which claim a further optimization on the protocol efficiency of DNP3.
An Enhanced Accident Detection And Victim Status Indicating System
In the speedy moving world, nobody is ready to look what's happening around them. Even when there occurs an accident nobody cares about it. This is an intention to implement an innovative solution for this problem by developing an Enhanced Accident detection System for Indicating Victim Status from the accident zone.
This system has been developed and implemented using the biomedical smart sensors and microcontroller based mobile technology integrated with the evolving LabVIEW platform. The system will automatically identify the accident, then immediately transmit the location of the accident and the status of the physiological parameters of the victims to the emergency care center phone number through Short Message Service (SMS).
The victim's physiological parameters such as body temperature, Heartbeat, Coma stage recovery status have been transmitted in the SMS. So the proposed system ensures that to reduce the human death ratio by accidents. When the accident occurs and realizes that there is no severe collision, then the person involved in accident has to press the switch provision which has been made to indicate that the accident is diminutive and no communication will be established i.e. no further alarming SMS has been transmitted.
This system has been developed and implemented using the biomedical smart sensors and microcontroller based mobile technology integrated with the evolving LabVIEW platform. The system will automatically identify the accident, then immediately transmit the location of the accident and the status of the physiological parameters of the victims to the emergency care center phone number through Short Message Service (SMS).
The victim's physiological parameters such as body temperature, Heartbeat, Coma stage recovery status have been transmitted in the SMS. So the proposed system ensures that to reduce the human death ratio by accidents. When the accident occurs and realizes that there is no severe collision, then the person involved in accident has to press the switch provision which has been made to indicate that the accident is diminutive and no communication will be established i.e. no further alarming SMS has been transmitted.
An experimental study of interference in Smart Buildings
Smart Building (SB) is a new and exciting concept in which multiple home appliances communicate with each other using short range wireless communication technologies, such as ZigBee, to create smart environments.
On the other hand, WiFi plays a leading role in providing wireless data coverage inside buildings and has been one of the most successful technologies of the past decade. However, the coexistence of WiFi and ZigBee is an issue in a SB environment due to excessive interference.
To ratify its importance in actual environments, we performed experiments with programmable ZigBee-Pro (ZBP) devices and WiFi routers at the University of Greenwich in Mobile and Wireless Communications Research Laboratory (MWCRL). In this paper, experimental results are presented and interference between ZigBee and WiFi networks is estimated. Based on our study, a recommendation is also made to reduce interference in SBs to improve users' quality of experience.
On the other hand, WiFi plays a leading role in providing wireless data coverage inside buildings and has been one of the most successful technologies of the past decade. However, the coexistence of WiFi and ZigBee is an issue in a SB environment due to excessive interference.
To ratify its importance in actual environments, we performed experiments with programmable ZigBee-Pro (ZBP) devices and WiFi routers at the University of Greenwich in Mobile and Wireless Communications Research Laboratory (MWCRL). In this paper, experimental results are presented and interference between ZigBee and WiFi networks is estimated. Based on our study, a recommendation is also made to reduce interference in SBs to improve users' quality of experience.
An Icing On-Line Monitoring System of Transmission Lines based on WSN
According to the erecting features of transmission lines and the monitoring data type, an icing on-line monitoring system of transmission lines based on WSNs is designed.
This paper presents a hierarchical wireless sensor network based on Zigbee technology, after analyzing the limitations of communication methods used by existing monitoring system. The bottom basic layer of the network is responsible for collecting the monitoring data, while the function of the top backbone layer is to relay data. By this way, the coverage of the network can be improved.
In this paper, the hardware and software of the nodes are designed, several key problems are discussed at the same time, such as the networking process and node's power supply.
This paper presents a hierarchical wireless sensor network based on Zigbee technology, after analyzing the limitations of communication methods used by existing monitoring system. The bottom basic layer of the network is responsible for collecting the monitoring data, while the function of the top backbone layer is to relay data. By this way, the coverage of the network can be improved.
In this paper, the hardware and software of the nodes are designed, several key problems are discussed at the same time, such as the networking process and node's power supply.
An indoor navigation approach to aid the physically disabled people
Physical disability becomes a major obstacle in the lives of physically challenged people and they are deprived of performing even their day-to-day activities without anybody's aid. One of the common problems they face is navigating their own home. So we proposed a system which aids such people to navigate their home or any indoor environment with all ease.
Using this system not only can they reach any desired room in their home, they could also reach to the commonly used places inside a room such as sofa, television, refrigerator or any such commonly used places using voice commands. This can be done using the indoor positioning technique. The given area of the house is mapped into the system. The user's location is triangulated by applying lateration techniques such as time difference of arrival and angle of arrival.
The location of the target places should be already marked which is essentially done using the same indoor positioning approach. A virtual line is drawn from the current location to the targeted location and the wheelchair is made to travel along the path calculating the coordinates dynamically and comparing with the already known coordinates of the line from the system thus making the wheelchair navigate correctly.
We also provide an obstacle avoidance technique suitable for this type of navigation which detects dynamic obstacles present in the real time environment. This proposed system can be of immense use to various physically disabled people and thus making their lives easy without any external aid.
Using this system not only can they reach any desired room in their home, they could also reach to the commonly used places inside a room such as sofa, television, refrigerator or any such commonly used places using voice commands. This can be done using the indoor positioning technique. The given area of the house is mapped into the system. The user's location is triangulated by applying lateration techniques such as time difference of arrival and angle of arrival.
The location of the target places should be already marked which is essentially done using the same indoor positioning approach. A virtual line is drawn from the current location to the targeted location and the wheelchair is made to travel along the path calculating the coordinates dynamically and comparing with the already known coordinates of the line from the system thus making the wheelchair navigate correctly.
We also provide an obstacle avoidance technique suitable for this type of navigation which detects dynamic obstacles present in the real time environment. This proposed system can be of immense use to various physically disabled people and thus making their lives easy without any external aid.
An In-home Medication Management Solution Based on Intelligent Packaging and Ubiquitous Sensing
A healthcare solution for medication noncompliance problem would help to save $177 billion annually in the United States. In addition, an in-home healthcare station (IHHS) is needed to meet the rapidly increasing demands for daily monitoring with on-site diagnosis and prognosis. In this paper, an intelligent medication management system is proposed based on intelligent package and ubiquitous sensing technologies.
Preventive medication management is enabled by an intelligent package sealed by Controlled Delamination Material (CDM) and controlled by RFID link. Various vital parameters are collected by wearable biomedical sensors through the short range wireless link. Onsite diagnosis and prognosis based on these health parameters are supported by the scalable architecture.
Additionally, friendly human-machine interface is emphasized to make it convenient for the elderly or disabled patients. A prototype system including the hardware, embedded software, user interface, database and some intelligent packages is implemented to verify the concepts.
Preventive medication management is enabled by an intelligent package sealed by Controlled Delamination Material (CDM) and controlled by RFID link. Various vital parameters are collected by wearable biomedical sensors through the short range wireless link. Onsite diagnosis and prognosis based on these health parameters are supported by the scalable architecture.
Additionally, friendly human-machine interface is emphasized to make it convenient for the elderly or disabled patients. A prototype system including the hardware, embedded software, user interface, database and some intelligent packages is implemented to verify the concepts.
An Innovative method of teaching electronic system design with PSoC
Programmable system-on-chip (PSoC), which provides a microprocessor and programmable analog and digital peripheral functions in a single chip, is very convenient for mixed-signal electronic system design.
This paper presents the experience of teaching contemporary mixed-signal electronic system design with PSoC in the Department of Automation, Tsinghua University, Beijing, China. An innovative teaching method was adopted, which involved designing a flexible experimental board, designing four experiments of different levels and with different teaching objectives, writing a textbook, and instructing students in out-of-class activities.
This paper describes these in detail, as well as the courses in which the method was used, with their course objectives and contents. Finally, the course evaluation results and the design prizes for innovation won by students and teaching awards won by teachers are given, which confirm that this innovative teaching method is effective.
This paper presents the experience of teaching contemporary mixed-signal electronic system design with PSoC in the Department of Automation, Tsinghua University, Beijing, China. An innovative teaching method was adopted, which involved designing a flexible experimental board, designing four experiments of different levels and with different teaching objectives, writing a textbook, and instructing students in out-of-class activities.
This paper describes these in detail, as well as the courses in which the method was used, with their course objectives and contents. Finally, the course evaluation results and the design prizes for innovation won by students and teaching awards won by teachers are given, which confirm that this innovative teaching method is effective.
An Integrated Health Management Process for Automotive Cyber-Physical Systems
Automobile is one of the most widely distributed cyber-physical systems. Over the last few years, the electronic explosion in automotive vehicles has significantly increased the complexity, heterogeneity and interconnectedness of embedded systems. Although designed to sustain long life, systems degrade in performance due to gradual development of anomalies eventually leading to faults.
In addition, system usage and operating conditions (e.g., weather, road surfaces, and environment) may lead to different failure modes that can affect the performance of vehicles. Advanced diagnosis and prognosis technologies are needed to quickly detect and isolate faults in network-embedded automotive systems so that proactive corrective maintenance actions can be taken to avoid failures and improve vehicle availability.
This paper discusses an integrated diagnostic and prognostic framework, and applies it to two automotive systems, viz., a Regenerative Braking System (RBS) in hybrid electric vehicles and an Electric Power Generation and Storage (EPGS) system.
In addition, system usage and operating conditions (e.g., weather, road surfaces, and environment) may lead to different failure modes that can affect the performance of vehicles. Advanced diagnosis and prognosis technologies are needed to quickly detect and isolate faults in network-embedded automotive systems so that proactive corrective maintenance actions can be taken to avoid failures and improve vehicle availability.
This paper discusses an integrated diagnostic and prognostic framework, and applies it to two automotive systems, viz., a Regenerative Braking System (RBS) in hybrid electric vehicles and an Electric Power Generation and Storage (EPGS) system.
An Integrated Two-Level Self-Calibration Method for a Cable-Driven Humanoid Arm
This paper addresses the kinematic calibration issues for a 7-DOF cable-driven humanoid arm in order to improve its motion control accuracy. The proposed 7-DOF humanoid arm has a hybrid parallel-serial kinematic structure, which consists of three serially connected parallel cable-driven modules, i.e., a 3-DOF shoulder module, a 1-DOF elbow module, and a 3-DOF wrist module. Due to the unique arm design features such as hybrid parallel-serial structure, modular configuration, and redundant sensors, an integrated two-level self-calibration method is proposed in this work.
The first level of self-calibration, termed as the central linkage mechanism calibration, is to identify the kinematics errors existed in the 7-DOF central linkage mechanism based on its self-motion capability. The second level of calibration, termed as the cable-driven module calibration, is to identify the kinematics errors existed in each of the parallel cable-driven modules based on its sensing redundancy.
To simplify the formulation of the calibration algorithms, the error model of the serial central linkage mechanism is derived from its forward kinematics, in which the Products-Of-Exponential (POE) formula is employed, while the error models of the parallel cable-driven modules are derived from their inverse kinematics.
The simulation and experimental results have shown that the proposed self-calibration algorithms can effectively improve the accuracy of the 7-DOF cable-driven humanoid arm.
The first level of self-calibration, termed as the central linkage mechanism calibration, is to identify the kinematics errors existed in the 7-DOF central linkage mechanism based on its self-motion capability. The second level of calibration, termed as the cable-driven module calibration, is to identify the kinematics errors existed in each of the parallel cable-driven modules based on its sensing redundancy.
To simplify the formulation of the calibration algorithms, the error model of the serial central linkage mechanism is derived from its forward kinematics, in which the Products-Of-Exponential (POE) formula is employed, while the error models of the parallel cable-driven modules are derived from their inverse kinematics.
The simulation and experimental results have shown that the proposed self-calibration algorithms can effectively improve the accuracy of the 7-DOF cable-driven humanoid arm.
An Intelligent System for Large-scale Disaster Behavior Analysis and Reasoning
Most severe disasters cause large human population movements and evacuations. Understanding and predicting these movements is critical for planning effective humanitarian relief, disaster management, and long-term societal reconstruction. In this paper, we present an intelligent system called DBAPRS for analyzing and simulating of human evacuation behaviors during large-scale disasters in Japan.
DBAPRS stores the GPS records from mobile devices used by approximately 1.6 million people throughout Japan from 1 August 2010 to 31 July 2011. By mining this enormous set of Auto-GPS mobile sensor data, the short-term and long-term evacuation behaviors during the Great East Japan Earthquake and the Fukushima nuclear accident throughout the whole country are able to be automatically discovered and analyzed. Meanwhile, DBAPRS utilizes the discovered evacuations to effectively learn a probabilistic model to better understand and simulate human mobility during the disasters.
Based on the training model, population mobility in various cities impacted by the disasters throughout Japan is able to be automatically simulated or predicted. On the basis of such kind of intelligent system, it is easy for us to find some new features or population mobility patterns after the recent severe earthquake, tsunami and release of radioactivity in Japan, which are likely to play a vital role in future disaster relief and management worldwide.
DBAPRS stores the GPS records from mobile devices used by approximately 1.6 million people throughout Japan from 1 August 2010 to 31 July 2011. By mining this enormous set of Auto-GPS mobile sensor data, the short-term and long-term evacuation behaviors during the Great East Japan Earthquake and the Fukushima nuclear accident throughout the whole country are able to be automatically discovered and analyzed. Meanwhile, DBAPRS utilizes the discovered evacuations to effectively learn a probabilistic model to better understand and simulate human mobility during the disasters.
Based on the training model, population mobility in various cities impacted by the disasters throughout Japan is able to be automatically simulated or predicted. On the basis of such kind of intelligent system, it is easy for us to find some new features or population mobility patterns after the recent severe earthquake, tsunami and release of radioactivity in Japan, which are likely to play a vital role in future disaster relief and management worldwide.
An Interactive RFID-based Bracelet for Airport Luggage Tracking System
Radio Frequency Identification (RFID) is a promising technology that has been implemented lately in airports. RFID tags are used to identify and track the location of passengers' luggage.
This paper investigates the use of an interactive bracelet that communicates with the RFID system by mean of a database application. The database system interacts with the bracelet using messages that inform the passenger about his luggage status.
The proposed database design and implementation are also discussed to describe the different functionalities of the application.
This paper investigates the use of an interactive bracelet that communicates with the RFID system by mean of a database application. The database system interacts with the bracelet using messages that inform the passenger about his luggage status.
The proposed database design and implementation are also discussed to describe the different functionalities of the application.
An investigation into voltage transformers used for tariff metering of medium and high voltage loads and standard guidelines for its application
For certain VT connections and unknown consumer earthing practices, metering errors will occur during unbalanced loading. Because of the small load offered by modern numerical tariff meters and relays, VT burden ratings may be inappropriate and the VT may not operate within its accuracy range.
This can give rise to the ferroresonance phenomenon and neutral inversion for certain system and VT conditions. VTs used for tariff metering were investigated based on limb design, parameters, earthing and connection methods. To compare the accuracy, case studies were created and calculations performed with the aid of an Excel iterative program. The calculations compared the actual real power supplied to a load with the real power seen by the voltage and current transformers.
From the results and theoretical research, optimum VT earthing, connections, ratings and standards were determined and compiled in a concise Code of Practice.
This can give rise to the ferroresonance phenomenon and neutral inversion for certain system and VT conditions. VTs used for tariff metering were investigated based on limb design, parameters, earthing and connection methods. To compare the accuracy, case studies were created and calculations performed with the aid of an Excel iterative program. The calculations compared the actual real power supplied to a load with the real power seen by the voltage and current transformers.
From the results and theoretical research, optimum VT earthing, connections, ratings and standards were determined and compiled in a concise Code of Practice.
An Optimal Power Scheduling Method for Demand Response in Home Energy Management System
With the development of smart grid, residents have the opportunity to schedule their power usage in the home by themselves for the purpose of reducing electricity expense and alleviating the power peak-to-average ratio (PAR).
In this paper, we first introduce a general architecture of energy management system (EMS) in a home area network (HAN) based on the smart grid and then propose an efficient scheduling method for home power usage. The home gateway (HG) receives the demand response (DR) information indicating the real-time electricity price that is transferred to an energy management controller (EMC).
With the DR, the EMC achieves an optimal power scheduling scheme that can be delivered to each electric appliance by the HG. Accordingly, all appliances in the home operate automatically in the most cost-effective way. When only the real-time pricing (RTP) model is adopted, there is the possibility that most appliances would operate during the time with the lowest electricity price, and this may damage the entire electricity system due to the high PAR. In our research, we combine RTP with the inclining block rate (IBR) model.
By adopting this combined pricing model, our proposed power scheduling method would effectively reduce both the electricity cost and PAR, thereby, strengthening the stability of the entire electricity system. Because these kinds of optimization problems are usually nonlinear, we use a genetic algorithm to solve this problem.
In this paper, we first introduce a general architecture of energy management system (EMS) in a home area network (HAN) based on the smart grid and then propose an efficient scheduling method for home power usage. The home gateway (HG) receives the demand response (DR) information indicating the real-time electricity price that is transferred to an energy management controller (EMC).
With the DR, the EMC achieves an optimal power scheduling scheme that can be delivered to each electric appliance by the HG. Accordingly, all appliances in the home operate automatically in the most cost-effective way. When only the real-time pricing (RTP) model is adopted, there is the possibility that most appliances would operate during the time with the lowest electricity price, and this may damage the entire electricity system due to the high PAR. In our research, we combine RTP with the inclining block rate (IBR) model.
By adopting this combined pricing model, our proposed power scheduling method would effectively reduce both the electricity cost and PAR, thereby, strengthening the stability of the entire electricity system. Because these kinds of optimization problems are usually nonlinear, we use a genetic algorithm to solve this problem.
An Optimized Wireless Sensor Network used in Video Surveillance System
This paper presents a new optimized method for wireless sensor network, which can be used in video surveillance systems. The new algorithm involves two steps. In the first step, the system integrates the time filtration and proportion of reliability weight, in order to intelligently merge and reinforce the results of kinds of sensors.
In the second step, it uses compressive sensing to confirm the alarm sensors. By these processes, the accuracy of target detection can be increased effectively, and the video surveillance system can only be switched on a region where some targets are detected. Therefore, it can save system resources, and enhance overall efficiency.
In the second step, it uses compressive sensing to confirm the alarm sensors. By these processes, the accuracy of target detection can be increased effectively, and the video surveillance system can only be switched on a region where some targets are detected. Therefore, it can save system resources, and enhance overall efficiency.
An RTOS-based Architecture for Industrial Wireless Sensor Network Stacks with Multi-Processor Support
The design of industrial wireless sensor network (IWSN) stacks requires the adoption of real time operation system (RTOS). Challenges exist especially in timing integrity and multi-processor support. As a solution, we propose an RTOS-based architecture for IWSN stacks with multi-processor support.
It offers benefits in terms of platform independency, product life cycle, safety and security, system integration complexity, and performance scalability. An implemented WirelessHART stack has proven the feasibility of the proposed architecture in practical product design. And future challenges as well as suggestions to standard improvement are discussed.
It offers benefits in terms of platform independency, product life cycle, safety and security, system integration complexity, and performance scalability. An implemented WirelessHART stack has proven the feasibility of the proposed architecture in practical product design. And future challenges as well as suggestions to standard improvement are discussed.
Analysis and design of an embedded system to aid the navigation of the visually impaired
This article aims to present the methodologies of development, analysis and system design of an Electronic Bengal, with object-oriented and structured methods, trying to establish the main features of these. From this scenario, several methods of system analysis are available for use.
Among the studies conducted to develop the system, using automation techniques, are SART (Structured Analysis Real-Time) and UML (Unified Modeling Language) modelings. Each has its peculiarities, both in the way of diagramming and about the script.
The project proposes an electronic device with an embedded system that contains a control algorithm to enable vibration and audio electromechanical transducers. The project is an electronic device based on open-source flexible platforms to assist in the orientation and mobility of the visually impaired during their displacement.
Among the studies conducted to develop the system, using automation techniques, are SART (Structured Analysis Real-Time) and UML (Unified Modeling Language) modelings. Each has its peculiarities, both in the way of diagramming and about the script.
The project proposes an electronic device with an embedded system that contains a control algorithm to enable vibration and audio electromechanical transducers. The project is an electronic device based on open-source flexible platforms to assist in the orientation and mobility of the visually impaired during their displacement.
ARM Hardware Platform for Vehicular Monitoring and Tracking
Design of Vehicular monitoring and tracking system based on ARM using GSM and GPM is proposed. The vehicular module is used to track, monitor, and surveillance and finds the accident spot and intimate to the monitoring station.
The proposed design provides information regarding vehicle Identity, speed, and position on real time basis. This information are collected by the ARM7 TDMI-S core processor LPC2148 by using different module and dispatch it to the monitoring station where it stores the information in database and display it on graphical user interface (GUI) that is user friendly. GUI is built on Microsoft Visual Studio 2010. This design provides information in real time using µc/OS-II.
The proposed design provides information regarding vehicle Identity, speed, and position on real time basis. This information are collected by the ARM7 TDMI-S core processor LPC2148 by using different module and dispatch it to the monitoring station where it stores the information in database and display it on graphical user interface (GUI) that is user friendly. GUI is built on Microsoft Visual Studio 2010. This design provides information in real time using µc/OS-II.
Assembly Strategies for Remanufacturing Systems with Variable Quality Returns
This paper studies optimal policy for modular product reassembly within a remanufacturing setting where a firm receives product returns with variable quality and reassembles products of multiple classes to customer orders. High-quality modules are allowed to substitute for low-quality modules during reassembly to provide the remanufacturing system with flexibility such that shortage in lower quality modules can be smoothed out by higher quality module inventories.
We formulate the problem as a Markov decision process and characterize the structure of the optimal control policy. In particular, we show that the optimal reassembly and substitution follow a state-dependent threshold-based control policy. We also establish the structural properties of the thresholds.
Using numerical experimentation, we study how system performance is influenced by key cost parameters including unit holding cost, unit assembly cost and shortage penalty cost.
Finally, we compare the optimal policy with an exhaustive reassembly policy and show that there is great benefit in module substitution and threshold-based assembly control.
We formulate the problem as a Markov decision process and characterize the structure of the optimal control policy. In particular, we show that the optimal reassembly and substitution follow a state-dependent threshold-based control policy. We also establish the structural properties of the thresholds.
Using numerical experimentation, we study how system performance is influenced by key cost parameters including unit holding cost, unit assembly cost and shortage penalty cost.
Finally, we compare the optimal policy with an exhaustive reassembly policy and show that there is great benefit in module substitution and threshold-based assembly control.
Audiovisual Voice Activity Detection based on Microphone Arrays and Color Information
Audiovisual voice activity detection is a necessary stage in several problems, such as advanced teleconferencing, speech recognition, and human-computer interaction. Lip motion and audio analysis provide a large amount of information that can be integrated to produce more robust audiovisual voice activity detection (VAD) schemes, as we discuss in this paper.
Lip motion is very useful for detecting the active speaker, and in this paper we introduce a new approach for lips and visual VAD. First, the algorithm performs skin segmentation to reduce the search area for lip extraction, and the most likely lip and non-lip regions are detected using a Bayesian approach within the delimited area.
Lip motion is then detected using Hidden Markov Models (HMMs) that estimate the likely occurrence of active speech within a temporal window. Audio information is captured by an array of microphones, and the sound-based VAD is related to finding spatio-temporally coherent sound sources through another set of HMMs.
To increase the robustness of the proposed system, a late fusion approach is employed to combine the result of each modality (audio and video). Our experimental results indicate that the proposed audiovisual approach presents better results when compared to existing VAD algorithms
Lip motion is very useful for detecting the active speaker, and in this paper we introduce a new approach for lips and visual VAD. First, the algorithm performs skin segmentation to reduce the search area for lip extraction, and the most likely lip and non-lip regions are detected using a Bayesian approach within the delimited area.
Lip motion is then detected using Hidden Markov Models (HMMs) that estimate the likely occurrence of active speech within a temporal window. Audio information is captured by an array of microphones, and the sound-based VAD is related to finding spatio-temporally coherent sound sources through another set of HMMs.
To increase the robustness of the proposed system, a late fusion approach is employed to combine the result of each modality (audio and video). Our experimental results indicate that the proposed audiovisual approach presents better results when compared to existing VAD algorithms
Automated Real-Time Detection of Potentially Suspicious Behavior in Public Transport Areas
Detection of suspicious activities in public transport areas using video surveillance has attracted an increasing level of attention. In general, automated offline video processing systems have been used for post-event analysis, such as forensics and riot investigations. However, very little has been achieved regarding real-time event recognition.
In this paper, we introduce a framework that processes raw video data received from a fixed color camera installed at a particular location, which makes real-time inferences about the observed activities.
First, the proposed framework obtains 3-D object-level information by detecting and tracking people and luggage in the scene using a real-time blob matching technique. Based on the temporal properties of these blobs, behaviors and events are semantically recognized by employing object and interobject motion features.
A number of types of behavior that are relevant to security in public transport areas have been selected to demonstrate the capabilities of this approach. Examples of these are abandoned and stolen objects, fighting, fainting, and loitering.
Using standard public data sets, the experimental results presented here demonstrate the outstanding performance and low computational complexity of this approach. We also discuss the advantages over other approaches in the literature.
In this paper, we introduce a framework that processes raw video data received from a fixed color camera installed at a particular location, which makes real-time inferences about the observed activities.
First, the proposed framework obtains 3-D object-level information by detecting and tracking people and luggage in the scene using a real-time blob matching technique. Based on the temporal properties of these blobs, behaviors and events are semantically recognized by employing object and interobject motion features.
A number of types of behavior that are relevant to security in public transport areas have been selected to demonstrate the capabilities of this approach. Examples of these are abandoned and stolen objects, fighting, fainting, and loitering.
Using standard public data sets, the experimental results presented here demonstrate the outstanding performance and low computational complexity of this approach. We also discuss the advantages over other approaches in the literature.
Automated Retail Store Based on RFID
Radio Frequency Identification (RFID) is one of the most exciting and promising technologies in the field of automated identification. This technology is being increasingly used in various areas such as supply-chain management, security, library, airline, military, animal farms, sports, etc. Common application examples are equipment tracking, personnel tracking, vehicle access controls, and items security in departmental stores.
Resource optimization, quality customer care, enhanced accuracy, and efficient business processes are the motivational factors behind the enormous use of RFID technology. In this paper, we present the design, development and implementation of an Automated Future Retail Store based on RFID technology.
Resource optimization, quality customer care, enhanced accuracy, and efficient business processes are the motivational factors behind the enormous use of RFID technology. In this paper, we present the design, development and implementation of an Automated Future Retail Store based on RFID technology.
Automated Urban drinking water supply control and water theft identification system
The rapid growing of the wide urban residential areas imposes the expansion as well as the modernization of the existing water supply facilities. Along with this one more problem is identified in the water supply channels, some people use ½ HP to 1 HP pump to suck the water directly from the channel of their home street.
Process automation system based upon utilization of an industrial PLC and PC systems including all the network components represents the best way to improve the water distribution technological process. The water theft can be best monitored by the flow variations given by the flow sensors mounted on the channels.
The system includes Remote Terminal Units - RTU, specific transducers and actuators distributed on a wide geographical area and control and power panels for the pump stations. The reliable instrumentation connected to PLC or RTU assure real time monitoring of the main technological parameters of large water distribution networks.
The data acquired of SCADA system (Supervisory Control and Data Acquisition) represent the support for optimization of the process and data- driven Decision Support System.
The system uses HMI implemented on PC to ensure the process supervision and remote control functions based on OPC technologies and wireless communication components for WAN data transfer. The complete SCADA system for water distribution enable the user to get a high operation safety of the network, a cost effective use of equipment, energy efficiency and optimize the daily operation and maintenance procedures.
Process automation system based upon utilization of an industrial PLC and PC systems including all the network components represents the best way to improve the water distribution technological process. The water theft can be best monitored by the flow variations given by the flow sensors mounted on the channels.
The system includes Remote Terminal Units - RTU, specific transducers and actuators distributed on a wide geographical area and control and power panels for the pump stations. The reliable instrumentation connected to PLC or RTU assure real time monitoring of the main technological parameters of large water distribution networks.
The data acquired of SCADA system (Supervisory Control and Data Acquisition) represent the support for optimization of the process and data- driven Decision Support System.
The system uses HMI implemented on PC to ensure the process supervision and remote control functions based on OPC technologies and wireless communication components for WAN data transfer. The complete SCADA system for water distribution enable the user to get a high operation safety of the network, a cost effective use of equipment, energy efficiency and optimize the daily operation and maintenance procedures.
Automatic Docking system for Recharging Home Surveillance Robots
This paper presents the development and characterization of a surveillance robot with automatic docking and recharging capabilities for home security. The proposed system is composed of a surveillance robot and a docking station. The palm-sized surveillance robot has a triangular shape with three wheels. It communicates with the general wireless home router through WiFi. It communicates with the docking station through ZigBee and serves as a mobile wireless sensor network gateway.
The docking station has a trapezoidal structure with an arc-shaped docking interface. A docking method based on the self-localization of the robot and the infrared detectors of the docking station is proposed.
The robot can return to the docking station for recharging operations when the on-board battery is too low. The experimental results show that the prototype robot achieved a success rate of 90% after 60 different docking attempts.
The docking station has a trapezoidal structure with an arc-shaped docking interface. A docking method based on the self-localization of the robot and the infrared detectors of the docking station is proposed.
The robot can return to the docking station for recharging operations when the on-board battery is too low. The experimental results show that the prototype robot achieved a success rate of 90% after 60 different docking attempts.
Automatic Lighting System Using Multiple Robotic Lamps
An automatic lighting system using 3-DOF robotic lamps and a laser scanner is proposed in this paper. The 3-DOF robotic lamp, which is designed with a spherical parallel mechanism with a unique forward kinematic solution, has a tilting motion to track a person and zoom-in and zoom-out motions to control the light intensity.
In order to minimize the dynamic load, three actuators are installed at the base frame, and a counterbalancing design is considered. The positions of people are detected by a laser scanner, and the Kalman filter and a data association algorithm are applied in order to track the positions of people accurately. Therefore, multiple robotic lamps can track and illuminate each person continuously.
We demonstrate experimentally that three robotic lamps mounted on the ceiling illuminate three people independently and control the intensity of the light according to the distance between a person and the robotic lamp.
In order to minimize the dynamic load, three actuators are installed at the base frame, and a counterbalancing design is considered. The positions of people are detected by a laser scanner, and the Kalman filter and a data association algorithm are applied in order to track the positions of people accurately. Therefore, multiple robotic lamps can track and illuminate each person continuously.
We demonstrate experimentally that three robotic lamps mounted on the ceiling illuminate three people independently and control the intensity of the light according to the distance between a person and the robotic lamp.
Automatic speed and torque monitoring in induction motor using zigbee and GSM.
This project is for monitoring the speed and torque in induction motors in real time by employing ZigBee based wireless sensor network. An embedded system is used for acquiring electrical signals from the motors in a noninvasive manner.
The processing for speed and torque estimation is done locally. Embedded system is used to control the speed of the motor. The values calculated by the embedded system are transmitted to a monitoring unit through ZigBee based wireless sensor network.
The real time monitoring of various motors can be done at the base unit. Speed of deployment, maintenance, low cost, security, reliability and throughput are the main advantages of using ZigBee. From simulation, plot for output voltage, output current, speed and torque can be obtained by applying different load values.
The processing for speed and torque estimation is done locally. Embedded system is used to control the speed of the motor. The values calculated by the embedded system are transmitted to a monitoring unit through ZigBee based wireless sensor network.
The real time monitoring of various motors can be done at the base unit. Speed of deployment, maintenance, low cost, security, reliability and throughput are the main advantages of using ZigBee. From simulation, plot for output voltage, output current, speed and torque can be obtained by applying different load values.
Automatic Weed Detection System and Smart Herbicide Sprayer Robot for corn fields
The goal of this paper is to develop a new weed detection and classification method that can be applied for autonomous weed control robots. In order to achieve this goal plants must be classified into crops and weeds according to their properties which is done by a machine vision algorithm.
Plants growing between rows are considered as weed, while inside a row, where crops are mixed with weeds, a classification method is required. Accordingly in the initial step, plants pixels were segmented from background with an adaptive method which is robust against variable light conditions as well as plant species. After that, crops and weeds were classified according to features extracted from wavelet analysis of the image.
Finally, based on positions of weeds, herbicide sprayers are told to spray right on desired spots. The whole algorithm is implemented in LabVIEW software which is appropriate for real-time in-field purposes. In order to evaluate the performance of the algorithm 73 corn field images have been taken and selected, overall classification accuracy of 95.89% was achieved
Plants growing between rows are considered as weed, while inside a row, where crops are mixed with weeds, a classification method is required. Accordingly in the initial step, plants pixels were segmented from background with an adaptive method which is robust against variable light conditions as well as plant species. After that, crops and weeds were classified according to features extracted from wavelet analysis of the image.
Finally, based on positions of weeds, herbicide sprayers are told to spray right on desired spots. The whole algorithm is implemented in LabVIEW software which is appropriate for real-time in-field purposes. In order to evaluate the performance of the algorithm 73 corn field images have been taken and selected, overall classification accuracy of 95.89% was achieved
Battery Energy Storage Station (BESS)-based Smoothing Control of Photovoltaic (PV) and Wind Power Generation Fluctuations
The battery energy storage station (BESS) is the current and typical means of smoothing wind- or solar-power generation fluctuations. Such BESS-based hybrid power systems require a suitable control strategy that can effectively regulate power output levels and battery state of charge (SOC).
This paper presents the results of a wind/photovoltaic (PV)/BESS hybrid power system simulation analysis undertaken to improve the smoothing performance of wind/PV/BESS hybrid power generation and the effectiveness of battery SOC control. A smoothing control method for reducing wind/PV hybrid output power fluctuations and regulating battery SOC under the typical conditions is proposed.
A novel real-time BESS-based power allocation method also is proposed. The effectiveness of these methods was verified using MATLAB/SIMULINK software
This paper presents the results of a wind/photovoltaic (PV)/BESS hybrid power system simulation analysis undertaken to improve the smoothing performance of wind/PV/BESS hybrid power generation and the effectiveness of battery SOC control. A smoothing control method for reducing wind/PV hybrid output power fluctuations and regulating battery SOC under the typical conditions is proposed.
A novel real-time BESS-based power allocation method also is proposed. The effectiveness of these methods was verified using MATLAB/SIMULINK software
Biometric Authentication using Mouse Gesture Dynamics
The mouse dynamics biometric is a behavioral biometric technology that extracts and analyzes the movement characteristics of the mouse input device when a computer user interacts with a graphical user interface for identification purposes.
Most of the existing studies on mouse dynamics analysis have targeted primarily continuous authentication or user reauthentication for which promising results have been achieved. Static authentication (at login time) using mouse dynamics, however, appears to face some challenges due to the limited amount of data that can reasonably be captured during such a process. In this paper, we present a new mouse dynamics analysis framework that uses mouse gesture dynamics for static authentication.
The captured gestures are analyzed using a learning vector quantization neural network classifier. We conduct an experimental evaluation of our framework with 39 users, in which we achieve a false acceptance ratio of 5.26% and a false rejection ratio of 4.59% when four gestures were combined, with a test session length of 26.9 s.
This is an improvement both in the accuracy and validation sample, compared to the existing mouse dynamics approaches that could be considered adequate for static authentication. Furthermore, to our knowledge, our work is the first to present a relatively accurate static authentication scheme based on mouse gesture dynamics.
Most of the existing studies on mouse dynamics analysis have targeted primarily continuous authentication or user reauthentication for which promising results have been achieved. Static authentication (at login time) using mouse dynamics, however, appears to face some challenges due to the limited amount of data that can reasonably be captured during such a process. In this paper, we present a new mouse dynamics analysis framework that uses mouse gesture dynamics for static authentication.
The captured gestures are analyzed using a learning vector quantization neural network classifier. We conduct an experimental evaluation of our framework with 39 users, in which we achieve a false acceptance ratio of 5.26% and a false rejection ratio of 4.59% when four gestures were combined, with a test session length of 26.9 s.
This is an improvement both in the accuracy and validation sample, compared to the existing mouse dynamics approaches that could be considered adequate for static authentication. Furthermore, to our knowledge, our work is the first to present a relatively accurate static authentication scheme based on mouse gesture dynamics.
Building a Smart Home System with WSN and Service Robot
Smart home environments have evolved to the point where everyday objects and devices at home can be networked to give the inhabitants new means to control them. Advances in digital electronics have enable the development of small in size and communicate in short distances sensor nodes. They are low-cost, low-power and multifunctional.
The sensor nodes consist of sensing, data processing, and communication components, leverage the idea of Wireless Sensor Networks (WSN) based on collaborative effort of a large number of nodes. There are a large number of reseaches dealing with WSN applications, but it is still possible to explored in WSN development and maintenance.
This paper examines the possibility of integration WSN and the service robots into a smart home application. The service robots can be considered to be mobile nodes that provide additional sensorial information, improve/repair the connectivity and collect information from wireless sensor nodes. On the other hand, the WSN can be considered as an extension of the sensorial capabilities of the robots and it can provide a smart environment for the service robots.
The sensor nodes consist of sensing, data processing, and communication components, leverage the idea of Wireless Sensor Networks (WSN) based on collaborative effort of a large number of nodes. There are a large number of reseaches dealing with WSN applications, but it is still possible to explored in WSN development and maintenance.
This paper examines the possibility of integration WSN and the service robots into a smart home application. The service robots can be considered to be mobile nodes that provide additional sensorial information, improve/repair the connectivity and collect information from wireless sensor nodes. On the other hand, the WSN can be considered as an extension of the sensorial capabilities of the robots and it can provide a smart environment for the service robots.
Calibration of Stochastic Computer Models using Stochastic Approximation Methods
Computer models are widely used to simulate real processes. Within the computer model, there always exist some parameters which are unobservable in the real process but need to be specified in the model.
The procedure to adjust these unknown parameters in order to fit the model to observed data and improve predictive capability is known as calibration. Practically, calibration is typically done manually. In this paper, we propose an effective and efficient algorithm based on the stochastic approximation (SA) approach that can be easily automated.
We first demonstrate the feasibility of applying stochastic approximation to stochastic computer model calibration and apply it to three stochastic simulation models. We compare our proposed SA approach with another direct calibration search method, the genetic algorithm.
The results indicate that our proposed SA approach performs equally as well in terms of accuracy and significantly better in terms of computational search time. We further consider the calibration parameter uncertainty in the subsequent application of the calibrated model and propose an approach to quantify it using asymptotic approximations.
The procedure to adjust these unknown parameters in order to fit the model to observed data and improve predictive capability is known as calibration. Practically, calibration is typically done manually. In this paper, we propose an effective and efficient algorithm based on the stochastic approximation (SA) approach that can be easily automated.
We first demonstrate the feasibility of applying stochastic approximation to stochastic computer model calibration and apply it to three stochastic simulation models. We compare our proposed SA approach with another direct calibration search method, the genetic algorithm.
The results indicate that our proposed SA approach performs equally as well in terms of accuracy and significantly better in terms of computational search time. We further consider the calibration parameter uncertainty in the subsequent application of the calibrated model and propose an approach to quantify it using asymptotic approximations.
Carbon Footprint and the Management of Supply Chains: Insights from Simple Models
Using relatively simple and widely used models, we illustrate how carbon emission concerns could be integrated into operational decision-making with regard to procurement, production, and inventory management.
We show how, by associating carbon emission parameters with various decision variables, traditional models can be modified to support decision-making that accounts for both cost and carbon footprint. We examine how the values of these parameters as well as the parameters of regulatory emission control policies affect cost and emissions.
We use the models to study the extent to which carbon reduction requirements can be addressed by operational adjustments, as an alternative (or a supplement) to costly investments in carbon-reducing technologies. We also use the models to investigate the impact of collaboration among firms within the same supply chain on their costs and carbon emissions and study the incentives firms might have in seeking such cooperation.
We provide a series of insights that highlight the impact of operational decisions on carbon emissions and the importance of operational models in evaluating the impact of different regulatory policies and in assessing the benefits of investments in more carbon efficient technologies. Note to Practitioners-Firms worldwide, responding to the threat of government legislation or to concerns raised by their own consumers or shareholders, are undertaking initiatives to reduce their carbon footprint. It is the conventional thinking that such initiatives will require either capital investments or a switch to more expensive sources of energy or input material.
In this paper, we show that firms could effectively reduce their carbon emissions without significantly increasing their costs by making only operational adjustments and by collaborating with other members of their supply chain. We describe optimization models that can be used by firms to support operational decision making and supply chain collaboration, whil- taking into account carbon emissions.
We analyze the effect of different emission regulations, including strict emission caps, taxes on emissions, cap-and-offset, and cap-and-trade, on supply chain management decisions. In particular, we show that the presence of emission regulation can significantly increase the value of supply chain collaboration.
We show how, by associating carbon emission parameters with various decision variables, traditional models can be modified to support decision-making that accounts for both cost and carbon footprint. We examine how the values of these parameters as well as the parameters of regulatory emission control policies affect cost and emissions.
We use the models to study the extent to which carbon reduction requirements can be addressed by operational adjustments, as an alternative (or a supplement) to costly investments in carbon-reducing technologies. We also use the models to investigate the impact of collaboration among firms within the same supply chain on their costs and carbon emissions and study the incentives firms might have in seeking such cooperation.
We provide a series of insights that highlight the impact of operational decisions on carbon emissions and the importance of operational models in evaluating the impact of different regulatory policies and in assessing the benefits of investments in more carbon efficient technologies. Note to Practitioners-Firms worldwide, responding to the threat of government legislation or to concerns raised by their own consumers or shareholders, are undertaking initiatives to reduce their carbon footprint. It is the conventional thinking that such initiatives will require either capital investments or a switch to more expensive sources of energy or input material.
In this paper, we show that firms could effectively reduce their carbon emissions without significantly increasing their costs by making only operational adjustments and by collaborating with other members of their supply chain. We describe optimization models that can be used by firms to support operational decision making and supply chain collaboration, whil- taking into account carbon emissions.
We analyze the effect of different emission regulations, including strict emission caps, taxes on emissions, cap-and-offset, and cap-and-trade, on supply chain management decisions. In particular, we show that the presence of emission regulation can significantly increase the value of supply chain collaboration.
Certificate less Remote Anonymous Authentication Schemes for Wireless Body Area Networks
Wireless body area network (WBAN) has been recognized as one of the promising wireless sensor technologies for improving healthcare service thanks to its capability of seamlessly and continuously exchanging medical information in real time. However, the lack of an clear in-depth defense line in such a new networking paradigm would make its potential users worry about the leakage of their private information, especially to those unauthenticated or even malicious adversaries.
In this paper, we present a pair of efficient and light-weight authentication protocols to enable remote WBAN users to anonymously enjoy healthcare service. In particular, our authentication protocols are rooted with a novel certificateless signature (CLS) scheme, which is computational efficient and provably secure against existential forgery on adaptively chosen message attack in the random oracle model. Also, our designs ensure that application or service providers have no privilege to disclose the real identities of users.
Even the network manager, which serves as private key generator in the authentication protocols, are prevented from impersonating legitimate users. The performance of our designs are evaluated through both theoretic analysis and experimental simulations, and the comparative studies demonstrate that they outperform the existing schemes in terms of better trade-off between desirable security properties and computational overhead, nicely meeting the needs of WBANs.
In this paper, we present a pair of efficient and light-weight authentication protocols to enable remote WBAN users to anonymously enjoy healthcare service. In particular, our authentication protocols are rooted with a novel certificateless signature (CLS) scheme, which is computational efficient and provably secure against existential forgery on adaptively chosen message attack in the random oracle model. Also, our designs ensure that application or service providers have no privilege to disclose the real identities of users.
Even the network manager, which serves as private key generator in the authentication protocols, are prevented from impersonating legitimate users. The performance of our designs are evaluated through both theoretic analysis and experimental simulations, and the comparative studies demonstrate that they outperform the existing schemes in terms of better trade-off between desirable security properties and computational overhead, nicely meeting the needs of WBANs.
Challenges and Opportunities for Securing Intelligent Transportation System
There has been considerable work addressing security in vehicular network systems for intelligent transportation system (ITS) usages. We examine the proposed security framework and solutions in this space. Our analysis leads to several key observations.
The current security work misses many practical ITS usage and security requirements, since it fails to consider practical economic models and critical ITS functional requirements as a control system. Consequently, the standardized ITS communication message authenticity solutions have little utility relative to addressing the real threats.
Furthermore, we analyzed the missing requirements for public key infrastructure support for secure vehicular communication. Based on our analysis, we call for future research directions in analyzing practical problems and designing solutions to secure vehicular communication in order to achieve its full potential
The current security work misses many practical ITS usage and security requirements, since it fails to consider practical economic models and critical ITS functional requirements as a control system. Consequently, the standardized ITS communication message authenticity solutions have little utility relative to addressing the real threats.
Furthermore, we analyzed the missing requirements for public key infrastructure support for secure vehicular communication. Based on our analysis, we call for future research directions in analyzing practical problems and designing solutions to secure vehicular communication in order to achieve its full potential
Characterization of Rice Paddies by a UAV-Mounted Miniature Hyperspectral Sensor System
A low-cost, small, lightweight hyperspectral sensor system that can be loaded onto small unmanned autonomous vehicle (UAV) platforms has been developed for the acquisition of aerial hyperspectral data. Safe and easy observation is possible under unstable illumination conditions by using lightweight and autonomous cruising.
The hyperspectral sensor system, equipped with a 256-band hyperspectral sensor covering a spectral range from 340-763 nm, a GPS and a data logger, is 400 g in total weight. The acquisition period for each sampling, 768 bytes, is 100 ms. The aerial hyperspectral data of rice paddies are collected under cloudy weather.
The flight altitude from the ground is 10 m, and the cruising speed is 2 m/s. The high-accuracy estimation of the chlorophyll densities is confirmed, even under unstable illumination conditions, by frequent monitoring of the illumination level and the chlorophyll indices, based on the red-edge (RE) and near infrared (NIR) spectral ranges.
The hyperspectral sensor system, equipped with a 256-band hyperspectral sensor covering a spectral range from 340-763 nm, a GPS and a data logger, is 400 g in total weight. The acquisition period for each sampling, 768 bytes, is 100 ms. The aerial hyperspectral data of rice paddies are collected under cloudy weather.
The flight altitude from the ground is 10 m, and the cruising speed is 2 m/s. The high-accuracy estimation of the chlorophyll densities is confirmed, even under unstable illumination conditions, by frequent monitoring of the illumination level and the chlorophyll indices, based on the red-edge (RE) and near infrared (NIR) spectral ranges.
Child Activity Recognition based on Cooperative Fusion Model of a Triaxial Accelerometer and a Barometric Pressure Sensor
This paper presents a child activity recognition approach using a single 3-axis accelerometer and a barometric pressure sensor worn on a waist of the body to prevent child accidents such as unintentional injuries at home. Labeled accelerometer data are collected from children of both sexes up to the age of 16 to 29 months.
To recognize daily activities, mean, standard deviation, and slope of time-domain features are calculated over sliding windows. In addition, the FFT analysis is adopted to extract frequency-domain features of the aggregated data, and then energy and correlation of acceleration data are calculated. Child activities are classified into 11 daily activities which are wiggling, rolling, standing still, standing up, sitting down, walking, toddling, crawling, climbing up, climbing down, and stopping.
The overall accuracy of activity recognition was 98.43% using only a single- wearable triaxial accelerometer sensor and a barometric pressure sensor with a support vector machine
To recognize daily activities, mean, standard deviation, and slope of time-domain features are calculated over sliding windows. In addition, the FFT analysis is adopted to extract frequency-domain features of the aggregated data, and then energy and correlation of acceleration data are calculated. Child activities are classified into 11 daily activities which are wiggling, rolling, standing still, standing up, sitting down, walking, toddling, crawling, climbing up, climbing down, and stopping.
The overall accuracy of activity recognition was 98.43% using only a single- wearable triaxial accelerometer sensor and a barometric pressure sensor with a support vector machine
Communication Networks of Domestic Small-Scale Renewable Energy Systems
With the smart grid revolution, each house will have the ability to generate their own energy needs locally through renewable energy systems such as photovoltaic (PV) and wind turbines (WT).
This paper presents the communication network architectures using both wireless and dedicated wired medium for monitoring and controlling the distributed energy systems (DES) including a small-scale WT and PV system. To monitor the condition of standalone system (PV and WT), the various types of sensors are used to collect different measurement data. The data transmission rate of each sensor is computed according to the sampling frequency.
For DES in grid connected mode, the communication network of micro grid system is configured by hybrid architecture (wired-wireless). Based on network topology and different network configuration, OPNET modeler is used to evaluate the performance in view of total end-to-end delay using three different technologies, Ethernet based, Wi-Fi-based and ZigBee-based architectures.
This paper presents the communication network architectures using both wireless and dedicated wired medium for monitoring and controlling the distributed energy systems (DES) including a small-scale WT and PV system. To monitor the condition of standalone system (PV and WT), the various types of sensors are used to collect different measurement data. The data transmission rate of each sensor is computed according to the sampling frequency.
For DES in grid connected mode, the communication network of micro grid system is configured by hybrid architecture (wired-wireless). Based on network topology and different network configuration, OPNET modeler is used to evaluate the performance in view of total end-to-end delay using three different technologies, Ethernet based, Wi-Fi-based and ZigBee-based architectures.
Conditional Privacy Preserving Security Protocol for NFC Applications
In recent years, various mobile terminals equipped with NFC (Near Field Communication) have been released. The combination of NFC with smart devices has led to widening the utilization range of NFC. It is expected to replace credit cards in electronic payment, especially.
In this regard, security issues need to be addressed to vitalize NFC electronic payment. The NFC security standards currently being applied require the use of user's public key at a fixed value in the process of key agreement. The relevance of the message occurs in the fixed elements such as the public key of NFC. An attacker can create a profile based on user's public key by collecting the associated messages. Through the created profile, users can be exposed and their privacy can be compromised.
In this paper, we propose conditional privacy protection methods based on pseudonyms to solve these problems. In addition, PDU (Protocol Data Unit) for conditional privacy is defined. Users can inform the other party that they will communicate according to the protocol proposed in this paper by sending the conditional privacy preserved PDU through NFC terminals.
The proposed method succeeds in minimizing the update cost and computation overhead by taking advantage of the physical characteristics of NFC1.
In this regard, security issues need to be addressed to vitalize NFC electronic payment. The NFC security standards currently being applied require the use of user's public key at a fixed value in the process of key agreement. The relevance of the message occurs in the fixed elements such as the public key of NFC. An attacker can create a profile based on user's public key by collecting the associated messages. Through the created profile, users can be exposed and their privacy can be compromised.
In this paper, we propose conditional privacy protection methods based on pseudonyms to solve these problems. In addition, PDU (Protocol Data Unit) for conditional privacy is defined. Users can inform the other party that they will communicate according to the protocol proposed in this paper by sending the conditional privacy preserved PDU through NFC terminals.
The proposed method succeeds in minimizing the update cost and computation overhead by taking advantage of the physical characteristics of NFC1.
Context Aware Driver Behavior Detection System in Intelligent Transportation Systems (ITS)
Vehicle Ad hoc Networks (VANET) emerged as an application of Mobile Ad hoc Networks (MANET), which use Dedicated Short Range Communication (DSRC) to allow vehicles in close proximity to communicate with each other, or to communicate with roadside equipment. Applying wireless access technology in vehicular environments has led to the improvement of road safety and a reduction in the number of fatalities caused by road accidents, through the development of road safety applications and facilitating information sharing between moving vehicles regarding the road.
This paper focuses on developing a novel and non-intrusive driver behaviour detection system using a context-aware system in VANET to detect abnormal behaviours exhibited by drivers, and to warn other vehicles on the road so as to prevent accidents from happening. A five-layer contextaware architecture is proposed which is able to collect contextual information about the driving environment, perform reasoning about certain and uncertain contextual information and react upon that information.
A probabilistic model based on Dynamic Bayesian Networks (DBN) for real time inferring four types of driving behaviour (normal, drunk, reckless and fatigue) by combining contextual information about the driver, vehicle and the environment is presented. The dynamic behaviour model can capture the static and the temporal aspects related to the behaviour of the driver, thus, leading to robust and accurate behaviour detection. The evaluation of behaviour detection using synthetic data proves the validity of our model and the importance of including contextual information about the driver, the vehicle and the environment.
This paper focuses on developing a novel and non-intrusive driver behaviour detection system using a context-aware system in VANET to detect abnormal behaviours exhibited by drivers, and to warn other vehicles on the road so as to prevent accidents from happening. A five-layer contextaware architecture is proposed which is able to collect contextual information about the driving environment, perform reasoning about certain and uncertain contextual information and react upon that information.
A probabilistic model based on Dynamic Bayesian Networks (DBN) for real time inferring four types of driving behaviour (normal, drunk, reckless and fatigue) by combining contextual information about the driver, vehicle and the environment is presented. The dynamic behaviour model can capture the static and the temporal aspects related to the behaviour of the driver, thus, leading to robust and accurate behaviour detection. The evaluation of behaviour detection using synthetic data proves the validity of our model and the importance of including contextual information about the driver, the vehicle and the environment.
Context-Adaptive Multimodal Wireless Sensor Network for Energy-Efficient Gas Monitoring
We present a wireless sensor network (WSN) for monitoring indoor air quality, which is crucial for people's comfort, health, and safety because they spend a large percentage of time in indoor environments. A major concern in such networks is energy efficiency because gas sensors are power-hungry, and the sensor node must operate unattended for several years on a battery power supply.
A system with aggressive energy management at the sensor level, node level, and network level is presented. The node is designed with very low sleep current consumption (only 8 µA), and it contains a metal oxide semiconductor gas sensor and a pyroelectric infrared (PIR) sensor.
Furthermore, the network is multimodal; it exploits information from auxiliary sensors, such as PIR sensors about the presence of people and from the neighbor nodes about gas concentration to modify the behavior of the node and the measuring frequency of the gas concentration. In this way, we reduce the nodes' activity and energy requirements, while simultaneously providing a reliable service.
To evaluate our approach and the benefits of the context-aware adaptive sampling, we simulate an application scenario which demonstrates a significant lifetime extension (several years) compared to the continuously-driven gas sensor. In March 2012, we deployed the WSN with 36 nodes in a four-story building and by now the performance has confirmed models and expectations.
A system with aggressive energy management at the sensor level, node level, and network level is presented. The node is designed with very low sleep current consumption (only 8 µA), and it contains a metal oxide semiconductor gas sensor and a pyroelectric infrared (PIR) sensor.
Furthermore, the network is multimodal; it exploits information from auxiliary sensors, such as PIR sensors about the presence of people and from the neighbor nodes about gas concentration to modify the behavior of the node and the measuring frequency of the gas concentration. In this way, we reduce the nodes' activity and energy requirements, while simultaneously providing a reliable service.
To evaluate our approach and the benefits of the context-aware adaptive sampling, we simulate an application scenario which demonstrates a significant lifetime extension (several years) compared to the continuously-driven gas sensor. In March 2012, we deployed the WSN with 36 nodes in a four-story building and by now the performance has confirmed models and expectations.
Contingency Planning Over Probabilistic Obstacle Predictions for Autonomous Road Vehicles
This paper presents a novel optimization-based path planner that is capable of planning multiple contingency paths to directly account for uncertainties in the future trajectories of dynamic obstacles. This planner addresses the particular problem of probabilistic collision avoidance for autonomous road vehicles that are required to safely interact, in close proximity, with other vehicles with unknown intentions.
The presented path planner utilizes an efficient spline-based trajectory representation and fast but accurate collision probability bounds to simultaneously optimize multiple continuous contingency paths in real time. These collision probability bounds are efficient enough for real-time evaluation, yet accurate enough to allow for practical close-proximity driving behaviors such as passing an obstacle vehicle in an adjacent lane.
An obstacle trajectory clustering algorithm is also presented to enable the path planner to scale to multiple-obstacle scenarios. Simulation results show that the contingency planner allows for a more aggressive driving style than planning a single path without compromising the overall safety of the robot.
The presented path planner utilizes an efficient spline-based trajectory representation and fast but accurate collision probability bounds to simultaneously optimize multiple continuous contingency paths in real time. These collision probability bounds are efficient enough for real-time evaluation, yet accurate enough to allow for practical close-proximity driving behaviors such as passing an obstacle vehicle in an adjacent lane.
An obstacle trajectory clustering algorithm is also presented to enable the path planner to scale to multiple-obstacle scenarios. Simulation results show that the contingency planner allows for a more aggressive driving style than planning a single path without compromising the overall safety of the robot.
Controlling a Human-Computer Interface System with a Novel Classification Method that uses Electrooculography Signals
Electrooculography (EOG) signals can be used to control human–computer interface (HCI) systems, if properly classified. The ability to measure and process these signals may help HCI users to overcome many of the physical limitations and inconveniences in daily life. However, there are currently no effective multidirectional classification methods for monitoring eye movements. Here, we describe a classification method used in a wireless EOG-based HCI device for detecting eye movements in eight directions.
This device includes wireless EOG signal acquisition components, wet electrodes and an EOG signal classification algorithm. The EOG classification algorithm is based on extracting features from the electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down-left, up-right, and down-right) and blinking.
The recognition and processing of these eight different features were achieved in real-life conditions, demonstrating that this device can reliably measure the features of EOG signals. This system and its classification procedure provide an effective method for identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions in the near future.
This device includes wireless EOG signal acquisition components, wet electrodes and an EOG signal classification algorithm. The EOG classification algorithm is based on extracting features from the electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down-left, up-right, and down-right) and blinking.
The recognition and processing of these eight different features were achieved in real-life conditions, demonstrating that this device can reliably measure the features of EOG signals. This system and its classification procedure provide an effective method for identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions in the near future.
Coordinated Control of the Bus Tie Switches and Power Supply Converters for Fault Protection in DC Microgrids
For dc microgrids, coordinated operation of electronic power converters and mechanical contactors can rapidly isolate short circuit faults while maintaining continuity of power to loads. The entire process—rapidly limiting current, deenergizing the bus, reconfiguring the bus via segmentizers or bus ties, and reenergizing the network—can be accomplished in milliseconds, during whicThis work embodies the overspeed protection and safe headway control into an iterative learning control (ILC) based train trajectory tracking algorithm to satisfy the high safety requirement of high-speed railways.
First, a D-type ILC scheme with overspeed protection is proposed. Then, a corresponding coordinated ILC scheme with multiple trains is studied to keep the safe headway. Finally, the control scheme under traction/braking force constraint is also considered for this proposed ILC-based train trajectory tracking strategy.
Rigorous theoretical analysis has shown that the proposed control schemes can guarantee the asymptotic convergence of train speed and position to its desired profiles without requirement of the physical model aside from some mild assumptions on the system. Effectiveness is further evaluated through simulations. h time diode-isolated load-side hold-up capacitors continue supplying power to critical loads.
For a wide range of systems, reconfiguration can be accomplished in 8–10 ms, which is fast enough to comply with requirements of CBEMA and IEEE standards on power quality. Reconfiguration time depends on the power system dimensions, the number of sources connected to the system, the system nominal voltage, and the performance of segmentizers.
First, a D-type ILC scheme with overspeed protection is proposed. Then, a corresponding coordinated ILC scheme with multiple trains is studied to keep the safe headway. Finally, the control scheme under traction/braking force constraint is also considered for this proposed ILC-based train trajectory tracking strategy.
Rigorous theoretical analysis has shown that the proposed control schemes can guarantee the asymptotic convergence of train speed and position to its desired profiles without requirement of the physical model aside from some mild assumptions on the system. Effectiveness is further evaluated through simulations. h time diode-isolated load-side hold-up capacitors continue supplying power to critical loads.
For a wide range of systems, reconfiguration can be accomplished in 8–10 ms, which is fast enough to comply with requirements of CBEMA and IEEE standards on power quality. Reconfiguration time depends on the power system dimensions, the number of sources connected to the system, the system nominal voltage, and the performance of segmentizers.
Coordinated Iterative Learning Control Schemes for Train Trajectory Tracking with Over speed Protection
This work embodies the overspeed protection and safe headway control into an iterative learning control (ILC) based train trajectory tracking algorithm to satisfy the high safety requirement of high-speed railways. First, a D-type ILC scheme with overspeed protection is proposed. Then, a corresponding coordinated ILC scheme with multiple trains is studied to keep the safe headway.
Finally, the control scheme under traction/braking force constraint is also considered for this proposed ILC-based train trajectory tracking strategy. Rigorous theoretical analysis has shown that the proposed control schemes can guarantee the asymptotic convergence of train speed and position to its desired profiles without requirement of the physical model aside from some mild assumptions on the system. Effectiveness is further evaluated through simulations.
Finally, the control scheme under traction/braking force constraint is also considered for this proposed ILC-based train trajectory tracking strategy. Rigorous theoretical analysis has shown that the proposed control schemes can guarantee the asymptotic convergence of train speed and position to its desired profiles without requirement of the physical model aside from some mild assumptions on the system. Effectiveness is further evaluated through simulations.
Correct-by-Construction and Optimal Synthesis of Beacon-Enabled Zigbee Network
In this paper we develop a formal approach for the synthesis of a cost-effective and correct-by-construction communication network (focusing on ZigBee wireless networks) subject to a set of end-to-end communication constraints of latency, bandwidth and error-rate, together with the constraints of the network protocols and the desired geographical placement of the network.
We also develop a software platform to implement the proposed approach for network synthesis, and apply it to a practical wireless network synthesis for centralized as well as distributed estimation application.
We also develop a software platform to implement the proposed approach for network synthesis, and apply it to a practical wireless network synthesis for centralized as well as distributed estimation application.
Crack detection by a climbing robot using image analysis
Cracking on surfaces as walls or roofs of a building results in a rapid deterioration of such structures. Access to these places is sometimes very difficult for people. One approach to solve such inconvenient is the use of climbing robots provided with sensing devices.
In this paper, we propose a computer vision system using image analysis for inspection. A stereo camera is mounted on the thorax of a hexapod robot, named Hex-piderix. The images are processed using a method described in this document. It is a method invariant to illumination to detect cracks in the surface.
Image is improved through the estimation and removal of lighting pattern, and then a thresholding is applied using Otsu method. Finally morphological operations are applied to extract crack information.
In this paper, we propose a computer vision system using image analysis for inspection. A stereo camera is mounted on the thorax of a hexapod robot, named Hex-piderix. The images are processed using a method described in this document. It is a method invariant to illumination to detect cracks in the surface.
Image is improved through the estimation and removal of lighting pattern, and then a thresholding is applied using Otsu method. Finally morphological operations are applied to extract crack information.
CSMA/CD Technique based Controller Area Network implementation for reducing error rate in automobile applications
The Controller Area Network (CAN) is a serial bus communications protocol developed by Bosch in the early 1980s. It defines a standard for efficient and reliable communication between sensor, actuator, controller, and other nodes in real-time applications. CAN is the de facto standard in a large variety of networked embedded control systems.
The early CAN development was mainly supported by the vehicle industry: CAN is found in a variety of passenger cars, trucks, boats, spacecraft, and other types of vehicles. The protocol is also widely used today in industrial automation and other areas of networked embedded control, with applications in diverse products such as production machinery, medical equipment, building automation, weaving machines, and wheelchairs.
The early CAN development was mainly supported by the vehicle industry: CAN is found in a variety of passenger cars, trucks, boats, spacecraft, and other types of vehicles. The protocol is also widely used today in industrial automation and other areas of networked embedded control, with applications in diverse products such as production machinery, medical equipment, building automation, weaving machines, and wheelchairs.
In the automotive industry, embedded control has grown from stand-alone systems to highly integrated and networked control systems [11, 7]. By networking electro-mechanical subsystems, it becomes possible to modularize functionalities and hardware, which facilitates reuse and adds capabilities. Fig. 1 shows an example of an electronic control unit (ECU) mounted on a diesel engine of a Scania truck.
The ECU handles the control of engine, turbo, fan, etc. but also the CAN communication. Combining networks and mechatronic modules makes it possible to reduce both the cabling and the number
The ECU handles the control of engine, turbo, fan, etc. but also the CAN communication. Combining networks and mechatronic modules makes it possible to reduce both the cabling and the number
Customized Ultra High Frequency Radio Frequency Identification Tags and Reader Antennas Enabling Reliable Mobile Robot Navigation
Passive radio frequency identification (RFID) is an emerging technology allowing the automatic identification of passive devices, called tags, when interrogated by RFID readers. Because of its reasonable cost and its ease of use, RFID is being adopted more and more in many contexts, including robotics, where it is used as supplementary support for the navigation and localization of robots.
Indeed, when an RFID reader placed on the robot reads a tag marking a certain map point, specific algorithms can be used to estimate tag and/or robot position. Nevertheless, in most literature, commercial RFID devices, not specifically thought of for robotic applications, are adopted, with consequent strong impact on overall system performance and robustness. In this paper, customized RFID reader antennas and platform-robust tags are designed and realized according to several requirements specifically individuated for the addressed application.
Moreover, the new hardware is tested in two practical cases related to tag and robot indoor localization, respectively. In spite of the use of rough-and-ready algorithms, the obtained results are impressive and demonstrate the goodness of the proposed solution.
Indeed, when an RFID reader placed on the robot reads a tag marking a certain map point, specific algorithms can be used to estimate tag and/or robot position. Nevertheless, in most literature, commercial RFID devices, not specifically thought of for robotic applications, are adopted, with consequent strong impact on overall system performance and robustness. In this paper, customized RFID reader antennas and platform-robust tags are designed and realized according to several requirements specifically individuated for the addressed application.
Moreover, the new hardware is tested in two practical cases related to tag and robot indoor localization, respectively. In spite of the use of rough-and-ready algorithms, the obtained results are impressive and demonstrate the goodness of the proposed solution.
Data-Based Modeling of Vehicle Crash using Adaptive Neural-Fuzzy Inference System
Vehicle crashes are considered to be events that are extremely complex to be analyzed from the mathematical point of view. In order to establish a mathematical model of a vehicle crash, one needs to consider various areas of research.
For this reason, to simplify the analysis and improve the modeling process, in this paper, a novel adaptive neurofuzzy inference system (ANFIS-based) approach to reconstruct kinematics of colliding vehicles is presented. A typical five-layered ANFIS structure is trained to reproduce kinematics (acceleration, velocity, and displacement) of a vehicle involved in an oblique barrier collision.
Subsequently, the same ANFIS structure is applied to simulate different types of collisions than the one which was used in the training stage. Finally, the simulation outcomes are compared with the results obtained by applying different modeling techniques. The reliability of the proposed method is evaluated thanks to this comparative analysis.
For this reason, to simplify the analysis and improve the modeling process, in this paper, a novel adaptive neurofuzzy inference system (ANFIS-based) approach to reconstruct kinematics of colliding vehicles is presented. A typical five-layered ANFIS structure is trained to reproduce kinematics (acceleration, velocity, and displacement) of a vehicle involved in an oblique barrier collision.
Subsequently, the same ANFIS structure is applied to simulate different types of collisions than the one which was used in the training stage. Finally, the simulation outcomes are compared with the results obtained by applying different modeling techniques. The reliability of the proposed method is evaluated thanks to this comparative analysis.
Decision Making and Finite-Time Motion Control for a Group of Robots
This paper deals with the problem of odor source localization by designing and analyzing a decision-control system (DCS) for a group of robots. In the decision level, concentration magnitude information and wind information detected by robots are used to predict a probable position of the odor source. Specifically, the idea of particle swarm optimization is introduced to give a probable position of the odor source in terms of concentration magnitude information.
Moreover, an observation model of the position of the odor source is built according to wind information, and a Kalman filter is used to estimate the position of the odor source, which is combined with the position obtained by using concentration magnitude information in order to make a decision on the position of the odor source. In the control level, two types of the finite-time motion control algorithms are designed; one is a finite-time parallel motion control algorithm, while the other is a finite-time circular motion control algorithm.
Precisely, a nonlinear finite-time consensus algorithm is first proposed, and a Lyapunov approach is used to analyze the finite-time convergence of the proposed consensus algorithm. Then, on the basis of the proposed finite-time consensus algorithm, a finite-time parallel motion control algorithm, which can control the group of robots to trace the plume and move toward the probable position of odor source, is derived.
Next, a finite-time circular motion control algorithm, which can enable the robot group to circle the probable position of the odor source in order to search for odor clues, is also developed. Finally, the performance capabilities of the proposed DCS are illustrated through the problem of odor source localization.
Moreover, an observation model of the position of the odor source is built according to wind information, and a Kalman filter is used to estimate the position of the odor source, which is combined with the position obtained by using concentration magnitude information in order to make a decision on the position of the odor source. In the control level, two types of the finite-time motion control algorithms are designed; one is a finite-time parallel motion control algorithm, while the other is a finite-time circular motion control algorithm.
Precisely, a nonlinear finite-time consensus algorithm is first proposed, and a Lyapunov approach is used to analyze the finite-time convergence of the proposed consensus algorithm. Then, on the basis of the proposed finite-time consensus algorithm, a finite-time parallel motion control algorithm, which can control the group of robots to trace the plume and move toward the probable position of odor source, is derived.
Next, a finite-time circular motion control algorithm, which can enable the robot group to circle the probable position of the odor source in order to search for odor clues, is also developed. Finally, the performance capabilities of the proposed DCS are illustrated through the problem of odor source localization.
Design and Development of Digital PID Controller for DC Motor Drive System using Embedded Platform for Mobile Robot
In Agriculture industry, plants are prone to diseases caused by pathogens and environment conditions and it is a prime cause to lose of revenue. It requires continuous monitoring of plants and environment parameters to overcome this problem. A mobile Robotic system for monitoring these parameters using wireless network has been envisaged here and developed based on ARM-Linux platform.
Robotic platform consists of ARM9 based S3C2440 processor from SAMSUNG and Linux Kernel , Motor driver, robot mechanical assembly. The farm environment and plant condition such as temperature, humidity soil moisture content etc. are continuously monitored through suitable data acquisition system incorporated in the robotic system. A servo motor based robotic arm is designed for collecting soil sample and test various soil parameters.
A closed loop feedback algorithm based on Digital PID controller has been developed for precise position and speed control of mobile robot. The wireless control of mobile robot and monitored data acquisition is accomplished using zigbee wireless protocol. For displaying acquired data on host system a Graphical user interface is designed using qt creater framework.
For independent functioning of mobile robot, application program is written in c language and cross compiled using arm-linux-gcc compiler on Ubuntu 10.04 platform and ported on the memory of ARM processor.
Robotic platform consists of ARM9 based S3C2440 processor from SAMSUNG and Linux Kernel , Motor driver, robot mechanical assembly. The farm environment and plant condition such as temperature, humidity soil moisture content etc. are continuously monitored through suitable data acquisition system incorporated in the robotic system. A servo motor based robotic arm is designed for collecting soil sample and test various soil parameters.
A closed loop feedback algorithm based on Digital PID controller has been developed for precise position and speed control of mobile robot. The wireless control of mobile robot and monitored data acquisition is accomplished using zigbee wireless protocol. For displaying acquired data on host system a Graphical user interface is designed using qt creater framework.
For independent functioning of mobile robot, application program is written in c language and cross compiled using arm-linux-gcc compiler on Ubuntu 10.04 platform and ported on the memory of ARM processor.
Design and Development Of PIC Microcontroller based Vehicle Monitoring System using Controller Area Network (CAN) Protocol
Controller Area Network (CAN) is an attractive alternative in the automotive and automation industries due to its ease in use, low cost and provided reduction in wiring complexity. It was developed by Robert Bosch for communication between various digital devices inside an automobile where heavy electrical interferences and mechanical vibrations are present.
This project is aimed at the implementation of CAN protocol using PIC for vehicle monitoring system. The main feature of the system includes monitoring of various vehicle parameters such as Temperature, presence of CO level in the exhaust, Battery Voltage and Light due to spark or fire. The software part is done in MPLab IDE using Embedded C. Schematic is prepared using OrCAD. Hardware is implemented and software porting is done.
This project is aimed at the implementation of CAN protocol using PIC for vehicle monitoring system. The main feature of the system includes monitoring of various vehicle parameters such as Temperature, presence of CO level in the exhaust, Battery Voltage and Light due to spark or fire. The software part is done in MPLab IDE using Embedded C. Schematic is prepared using OrCAD. Hardware is implemented and software porting is done.
Design and Implementation of a Web-Service-Based Public-Oriented Personalized Health Care Platform
The use of information technology and management systems for the betterment of health care is more and more important and popular. However, existing efforts mainly focus on informatization of hospitals or medical institutions within the organizations, and few are directly oriented to the patients, their families, and other ordinary people.
The strong demand for various medical and public health care services from customers calls for the creation of powerful individual-oriented personalized health care service systems. Service computing and related technologies can greatly help one in fulfilling this task. In this paper, we present PHISP: a Public-oriented Health care Information Service Platform, which is based on such technologies. It can support numerous health care tasks, provide individuals with many intelligent and personalized services, and support basic remote health care and guardianship.
In order to realize the personalized customization and active recommendation of intelligent services for individuals, several key techniques for service composition are integrated, which can support branch and parallel control structures in the process models of composite services and are highlighted in this paper.
The strong demand for various medical and public health care services from customers calls for the creation of powerful individual-oriented personalized health care service systems. Service computing and related technologies can greatly help one in fulfilling this task. In this paper, we present PHISP: a Public-oriented Health care Information Service Platform, which is based on such technologies. It can support numerous health care tasks, provide individuals with many intelligent and personalized services, and support basic remote health care and guardianship.
In order to realize the personalized customization and active recommendation of intelligent services for individuals, several key techniques for service composition are integrated, which can support branch and parallel control structures in the process models of composite services and are highlighted in this paper.
Design and implementation of intelligent energy distribution management with photovoltaic system
As increasing power consumption is becoming a huge problem, renewable energy has been highlighted recently. Many companies and research centers study this new sustainable energy, and various products have appeared to the public.
However, this kind of researches concentrates on the elemental technologies, and now a management system is needed to manage these technologies to maximize energy efficiency.
In this paper, we propose the system of Intelligent Energy Distribution Management (iEDM) to monitor fast-changing environmental variables and manage solar power flexibly. Compared with normal utility interactive systems, the iEDM improves the energy efficiency up to 5.6 percent.
However, this kind of researches concentrates on the elemental technologies, and now a management system is needed to manage these technologies to maximize energy efficiency.
In this paper, we propose the system of Intelligent Energy Distribution Management (iEDM) to monitor fast-changing environmental variables and manage solar power flexibly. Compared with normal utility interactive systems, the iEDM improves the energy efficiency up to 5.6 percent.
Design and implementation of Real Time Embedded Tele-Health Monitoring system
Now a day's healthcare industry is to provide better healthcare to people anytime and anywhere in the world in a more economic and patient friendly manner. In the present paper the physiological parameters such as ECG, Pulse rate and Temperature are obtained, processed using ARM7 LPC 2138 processor and displayed in a MATLAB graphical user interface. If any vital parameter goes out of normal range then alert SMS will be sent to Doctor Mobile. T
his system is utilizing Teamviewer software and low cost component to transmit ECG data to physicians for monitoring, diagnosis and patients care at a significantly low cost, regardless of patient's location.
his system is utilizing Teamviewer software and low cost component to transmit ECG data to physicians for monitoring, diagnosis and patients care at a significantly low cost, regardless of patient's location.
Design of a Low-Power On-Body ECG Classifier for Remote Cardiovascular Monitoring Systems
In this paper, we first present a detailed study on the trade-off between the computational complexity (directly related to the power consumption) and classification accuracy for a number of classifiers for classifying normal and abnormal electrocardiograms (ECGs). In our analysis, we consider the spectral energy of the constituent waves of the ECG as the discriminative feature.
Starting with the exhaustive exploration of single heartbeat-based classification to ascertain the complexity-accuracy trade-off in different classification algorithms, we then extend our study for multiple heartbeat-based classification. We use data available in Physionet as well as samples from Southampton General Hospital Cardiology Department for our investigation. Our primary conclusion is that a classifier based on linear discriminant analysis (LDA) achieves comparable level of accuracy to the best performing support vector machine classifiers with advantage of significantly reduced computational complexity.
Subsequently, we propose an ultra low-power circuit implementation of the LDA classifier that could be integrated with the ECG sensor node enabling on-body normal and abnormal ECG classification. The simulated circuit is synthesized at 130 nm technology and occupies 0.70 mm2 of silicon area (0.979 mm2 after place and route) while it consumes 182.94 nW @ 1.08 V, estimated with Synopsys PrimeTime when operating at 1 KHz. These results clearly demonstrate the potential for low-power implementation of the proposed design.
Starting with the exhaustive exploration of single heartbeat-based classification to ascertain the complexity-accuracy trade-off in different classification algorithms, we then extend our study for multiple heartbeat-based classification. We use data available in Physionet as well as samples from Southampton General Hospital Cardiology Department for our investigation. Our primary conclusion is that a classifier based on linear discriminant analysis (LDA) achieves comparable level of accuracy to the best performing support vector machine classifiers with advantage of significantly reduced computational complexity.
Subsequently, we propose an ultra low-power circuit implementation of the LDA classifier that could be integrated with the ECG sensor node enabling on-body normal and abnormal ECG classification. The simulated circuit is synthesized at 130 nm technology and occupies 0.70 mm2 of silicon area (0.979 mm2 after place and route) while it consumes 182.94 nW @ 1.08 V, estimated with Synopsys PrimeTime when operating at 1 KHz. These results clearly demonstrate the potential for low-power implementation of the proposed design.
Design of an Intelligent Electric Vehicle for Blind
As the technology increases we can solve many problems of the people. There are lots of persons who cannot walk very easily due to blindness. For them travelling with safety is a major problem. An intelligent electric vehicle is thus required to solve their problem.
The vehicle is made with a lot of technologies such as Digital image processing for obstacle detection, edge detection and road detection, Sonar, Infrared and Lidar based Obstacle avoidance, GPS and Map based location guidance for vehicle, GSM based emergency servicing and semi automatic control system for vehicle.
We propose a design of completely intelligent electric vehicle for blind which can be implemented successfully. The vehicle is designed in such a way that it can climb footpaths. The vehicle is designed to obey all traffic signals so that the design is apt for real world.
The vehicle is made with a lot of technologies such as Digital image processing for obstacle detection, edge detection and road detection, Sonar, Infrared and Lidar based Obstacle avoidance, GPS and Map based location guidance for vehicle, GSM based emergency servicing and semi automatic control system for vehicle.
We propose a design of completely intelligent electric vehicle for blind which can be implemented successfully. The vehicle is designed in such a way that it can climb footpaths. The vehicle is designed to obey all traffic signals so that the design is apt for real world.
Design of Emergency Remote Security Monitoring and control system based on ARM and Zigbee
In recent years, the home environment has seen a rapid introduction of network enabled digital technology. This technology offers new and exciting opportunities to increase the connectivity of devices within the home for the purpose of home automation. Moreover, with the rapid expansion of the Internet, there is the added potential for the remote control and monitoring of such network enabled devices. However, the adoption of home automation systems has been slow.
This paper identifies the reasons for this slow adoption and evaluates the potential of ZigBee for addressing these problems through the design and implementation of a flexible home automation architecture. A ZigBee based home automation system and Wi-Fi network are integrated through a common home gateway. The home gateway provides network interoperability, a simple and flexible user interface, and remote access to the system.
A dedicated virtual home is implemented to cater for the system's security and safety needs. To demonstrate the feasibility and effectiveness of the proposed system, four devices, a light switch, radiator valve, safety sensor and ZigBee remote control have been developed and evaluated with the home automation system.
This paper identifies the reasons for this slow adoption and evaluates the potential of ZigBee for addressing these problems through the design and implementation of a flexible home automation architecture. A ZigBee based home automation system and Wi-Fi network are integrated through a common home gateway. The home gateway provides network interoperability, a simple and flexible user interface, and remote access to the system.
A dedicated virtual home is implemented to cater for the system's security and safety needs. To demonstrate the feasibility and effectiveness of the proposed system, four devices, a light switch, radiator valve, safety sensor and ZigBee remote control have been developed and evaluated with the home automation system.
Design of Milk Analysis Embedded System for Dairy Farmers
In recent years the National Dairy Development Board-initiated cooperative movement has led to a substantial increase in milk production in India. The two main reasons for this increase are the efficient collection of milk and higher profit for the producers, both of which have to some degree been influenced by information technology.
The appropriate information technology described in this paper helped to make information symmetric in the market, thereby minimizing problems of adverse selection and tedious work. It is only recently that automation has been introduced into agriculture. In many dairy farms, computer aided control of physiological and sanitary parameters are already used and lead to a productivity increase and the elimination of some tedious operations.
Embedded Technology is now in its prime and the wealth of knowledge available is mind-blowing. An embedded system can be defined as a control system or computer system designed to perform a specific task. Embedded systems are playing important roles in our lives every day, even though they might not necessarily be visible. This paper describes one of the applications of embedded system MILKOTESTER. It is Small compact, embedded in a single unit, requires less power and measure milk parameters like SNF (Solid but Not FAT), FAT, CLR, WEIGHT, PH, with less cost
The appropriate information technology described in this paper helped to make information symmetric in the market, thereby minimizing problems of adverse selection and tedious work. It is only recently that automation has been introduced into agriculture. In many dairy farms, computer aided control of physiological and sanitary parameters are already used and lead to a productivity increase and the elimination of some tedious operations.
Embedded Technology is now in its prime and the wealth of knowledge available is mind-blowing. An embedded system can be defined as a control system or computer system designed to perform a specific task. Embedded systems are playing important roles in our lives every day, even though they might not necessarily be visible. This paper describes one of the applications of embedded system MILKOTESTER. It is Small compact, embedded in a single unit, requires less power and measure milk parameters like SNF (Solid but Not FAT), FAT, CLR, WEIGHT, PH, with less cost
Design of the Smart Home Based on Embedded System
Smart home is a house that uses information technology to monitor the environment, control the electric appliance and communicates with the outer world. Smart home is a complex technology, at the same time it is developing. A sample house environment monitor and control system that is one branch of the Smart home is addressed in this paper. The system is based on the embedded system and can act as a security guard of the home.
The system can monitor the temperature, humidity, gas density, water immersion of the house and have infrared sensor to guarantees the family security. The system also has network and telephone connection to receive the owner's command and send the alert to the owner. The whole system includes a main control unit and input/output unit. The main chip of the main control unit is the S3C44B0X that is a 16/32 bits RISC processor and based on ARM7 core.
In the main control unit, the use of 5 inch LCD and the touch screen provide a well user interface for handlers, the LAN/telephone interface provide the tools to communication. The muC/OS-II software core manages the whole unit work as a whole system. The input unit includes many sensors and its circuit, the information form the input unit is a base of the main control unit. The output is the action part of the main control unit it drives the alert and the switch of the electric appliance
The system can monitor the temperature, humidity, gas density, water immersion of the house and have infrared sensor to guarantees the family security. The system also has network and telephone connection to receive the owner's command and send the alert to the owner. The whole system includes a main control unit and input/output unit. The main chip of the main control unit is the S3C44B0X that is a 16/32 bits RISC processor and based on ARM7 core.
In the main control unit, the use of 5 inch LCD and the touch screen provide a well user interface for handlers, the LAN/telephone interface provide the tools to communication. The muC/OS-II software core manages the whole unit work as a whole system. The input unit includes many sensors and its circuit, the information form the input unit is a base of the main control unit. The output is the action part of the main control unit it drives the alert and the switch of the electric appliance
Designing a Sustainable and Distributed Generation System for Semiconductor Wafer Fabs
Driven by wind and solar photovoltaics technology, the power industry is shifting towards a distributed generation (DG) paradigm. A key challenge in deploying a renewable DG system is the power volatility.
This study proposes a visionary energy concept and further presents a mathematical model that could help the large industry consumers adopt this new energy technology. The study seeks to design a grid-connected DG system that is capable of providing the necessary electricity for wafer fabs.
Simulation-based optimization algorithm was applied to determine the equipment type and capacity aiming to minimize the DG lifecycle cost. The proposed method was demonstrated on fab facilitates located in three different regions in the US.
This study proposes a visionary energy concept and further presents a mathematical model that could help the large industry consumers adopt this new energy technology. The study seeks to design a grid-connected DG system that is capable of providing the necessary electricity for wafer fabs.
Simulation-based optimization algorithm was applied to determine the equipment type and capacity aiming to minimize the DG lifecycle cost. The proposed method was demonstrated on fab facilitates located in three different regions in the US.
Deterministic and event triggered MAC protocol for industrial wireless networks
Recent years have endorsed momentous development in the industrial wireless sensor and actuator networks (IWSN) for real time communication. For industrial automation application these wireless networks like ZigBee and wireless HART indeed propose advantages in term of cost and flexibility, but the price to be paid is lower reliability in term of unpredictable delay time and lower throughput.
In this paper a new mechanism known as wireless arbitration, is proposed for the nodes to access medium in the wireless sensor and actuator network according to their priority. In this new mechanism a specific arbitration frequency is allotted to each node according to the priority of the node in the network, so the node interested to access the medium will transmit its frequency for a fixed amount of time, and all the transmitted frequencies will be received by each node.
The received frequencies will then be compared to give the medium access to the high priority node. This mechanism makes the delay deterministic by allocating the medium to the highest priority node in fixed arbitration time, which improves maximum throughput, minimum delay and bandwidth efficiency with allowing event based medium access.
In this paper a new mechanism known as wireless arbitration, is proposed for the nodes to access medium in the wireless sensor and actuator network according to their priority. In this new mechanism a specific arbitration frequency is allotted to each node according to the priority of the node in the network, so the node interested to access the medium will transmit its frequency for a fixed amount of time, and all the transmitted frequencies will be received by each node.
The received frequencies will then be compared to give the medium access to the high priority node. This mechanism makes the delay deterministic by allocating the medium to the highest priority node in fixed arbitration time, which improves maximum throughput, minimum delay and bandwidth efficiency with allowing event based medium access.
Developing a NFC based Patient Identification and Ward Round System for Mobile Devices using the Android Platform
We developed a mobile ward round system based on openEHR for the use on smartphones and tablet computers using the Android platform which integrates and uses NFC to explore new ways of computer interaction, data processing and workflows in the medical world.
Based on the automatic patient identification via NFC using the mobile device, physicians can easily view recent ward round results and edit/add information without manually selecting the patient from a list. The application mainly shows new ideas and possibilities to improve medical workflows and usability and how mobile devices can make use of existing frameworks and backend services.
Relying on the openEHR standard, physicians are not limited to a certain ward round document anymore but can define their own ward round templates by means of the openEHR templates and archetypes.
Based on the automatic patient identification via NFC using the mobile device, physicians can easily view recent ward round results and edit/add information without manually selecting the patient from a list. The application mainly shows new ideas and possibilities to improve medical workflows and usability and how mobile devices can make use of existing frameworks and backend services.
Relying on the openEHR standard, physicians are not limited to a certain ward round document anymore but can define their own ward round templates by means of the openEHR templates and archetypes.
Development and Evaluation of Object-Based Visual Attention for Automatic Perception of Robots
Bottom-up visual attention is an automatic behavior to guide visual perception to a conspicuous object in a scene. This paper develops a new object-based bottom-up attention (OBA) model for robots. This model includes four modules: Extraction of preattentive features, preattentive segmentation, estimation of space-based saliency, and estimation of proto-object-based saliency.
In terms of computation, preattentive segmentation serves as a bridge to connect the space-based saliency and object-based saliency. This paper therefore proposes a preattentive segmentation algorithm, which is able to self-determine the number of proto-objects, has low computational cost, and is robust in a variety of conditions such as noise and spatial transformations.
Experimental results have shown that the proposed OBA model outperforms space-based attention model and other object-based attention methods in terms of accuracy of attentional selection, consistency under a series of noise settings and object completion.
In terms of computation, preattentive segmentation serves as a bridge to connect the space-based saliency and object-based saliency. This paper therefore proposes a preattentive segmentation algorithm, which is able to self-determine the number of proto-objects, has low computational cost, and is robust in a variety of conditions such as noise and spatial transformations.
Experimental results have shown that the proposed OBA model outperforms space-based attention model and other object-based attention methods in terms of accuracy of attentional selection, consistency under a series of noise settings and object completion.
Development of a magnetic control system for an electric wheelchair using the tongue
One of the most important problems for patients with severe disability is the control systems for electric wheelchairs, because they cannot use common systems as the joystick or keypads.
This paper proposes the development of a magnetic control system (MCS) to handle a power wheelchair as an alternative control system for patients with spinal cord injuries, as quadriplegics.
The proposed system uses the movements of the patient's tongue to operate the power wheelchair, and also includes the development of new communication protocols for the wheelchair through a microcontroller, bridge H and magnetic control.
This paper proposes the development of a magnetic control system (MCS) to handle a power wheelchair as an alternative control system for patients with spinal cord injuries, as quadriplegics.
The proposed system uses the movements of the patient's tongue to operate the power wheelchair, and also includes the development of new communication protocols for the wheelchair through a microcontroller, bridge H and magnetic control.
Development of a Residential Appliance Control Interface (ACI) Module using Smart Systems
Smart system pilot projects provide for valuable lessons learnt in terms of demand response programs. These programs are an important safety net until new capacity comes online in South Africa. Strategies within the demand response programs include time of use tariff and real time load limiting schemes.
Appliance control technologies can assist users that are part of these programs in managing loads. One approach to appliance control is using off the shelf home automation technologies that provide for automatic load control.
This can be done with smart systems which provide the control signals in real time to the home automation devices. An interface module is required between the smart system and the home automation units. A simple interface unit was developed under Eskom Research. This interface provides for automated switching but does not provide for any intelligent load sensing. This is left for further development.
Appliance control technologies can assist users that are part of these programs in managing loads. One approach to appliance control is using off the shelf home automation technologies that provide for automatic load control.
This can be done with smart systems which provide the control signals in real time to the home automation devices. An interface module is required between the smart system and the home automation units. A simple interface unit was developed under Eskom Research. This interface provides for automated switching but does not provide for any intelligent load sensing. This is left for further development.
Development of a Wireless Sensor for the Measurement of Chicken Blood Flow Using the Laser Doppler Blood Flow Meter Technique
Here, we report the development of an integrated laser Doppler blood flow micrometer for chickens. This sensor weighs only 18 g and is one of the smallest-sized blood flow meters, with no wired line, these are features necessary for attaching the sensor to the chicken.
The structure of the sensor chip consists of two silicon cavities with a photo diode and a laser diode, which was achieved using the microelectromechanical systems technique, resulting in its small size and significantly low power consumption.
In addition, we introduced an intermittent measuring arrangement in the measuring system to reduce power consumption and to enable the sensor to work longer. We were successfully able to measure chicken blood flow for five consecutive days, and discovered that chicken blood flow shows daily fluctuations.
The structure of the sensor chip consists of two silicon cavities with a photo diode and a laser diode, which was achieved using the microelectromechanical systems technique, resulting in its small size and significantly low power consumption.
In addition, we introduced an intermittent measuring arrangement in the measuring system to reduce power consumption and to enable the sensor to work longer. We were successfully able to measure chicken blood flow for five consecutive days, and discovered that chicken blood flow shows daily fluctuations.
Development of Biomedical Data Acquisition System in Hard Real-Time Linux Environment
This paper proposes a data acquisition (DAQ) system for the bio signals which is based on the use of biosensors, signal processing unit, data acquisition card and computing device. The methodologies of developing a biomedical experimental set up for measurement, monitoring, recording bio-signal during animal testing in laboratory is presented. The device will be responsible for getting data through 16 channels.
The channels will be connected with the biosensors through which the signals of different biological state (e.g. Electrocardiograph, Blood pressure etc.) of human or animal body will be retrieved. Obtaining the signals from biosensors data acquisition process will be done in a signal processing system and that will convert the resulting samples into numeric values which can be manipulated by the software.
The signal data acquisition processing will be accomplished on Hard Real-Time Linux (RT-Linux) environment which will be presented through Graphical User Interface (GUI) developed in non RT-Linux environment. Linking between hard real time and non real time Linux will be done through Inter Process Communication (IPC) between two kernels.
The channels will be connected with the biosensors through which the signals of different biological state (e.g. Electrocardiograph, Blood pressure etc.) of human or animal body will be retrieved. Obtaining the signals from biosensors data acquisition process will be done in a signal processing system and that will convert the resulting samples into numeric values which can be manipulated by the software.
The signal data acquisition processing will be accomplished on Hard Real-Time Linux (RT-Linux) environment which will be presented through Graphical User Interface (GUI) developed in non RT-Linux environment. Linking between hard real time and non real time Linux will be done through Inter Process Communication (IPC) between two kernels.
Developments of the in-home display systems for residential energy monitoring
In order to efficiently reduce the amount of the electricity usage in the residential area, the demand response (DR) of the consumers is of importance. The in-home display (IHD) system provides energy monitoring information for the consumer DR.
Recently, we have developed several types of IHD systems, which are based on 2.4GHz ZigBee, the power line communication technique, and the suion model. Simulation results using realistic models show significant performance improvements compared to the scheme that does not dynamically refine correlation.
Recently, we have developed several types of IHD systems, which are based on 2.4GHz ZigBee, the power line communication technique, and the suion model. Simulation results using realistic models show significant performance improvements compared to the scheme that does not dynamically refine correlation.
Downlink Scheduling with Transmission Strategy Selection for Multi-Cell Mimo Systems
In this paper, we study downlink scheduling with transmission strategy selection in multi-cell multiple-input multiple-output (MIMO) systems. Depending on the level of inter-cell interference experienced by a user, the scheduler can choose between two MIMO transmission strategies, namely, spatial multiplexing and interference alignment.
We formulate an optimization problem which aims to jointly select a user and the corresponding transmission strategy for each base station in order to maximize the overall system utility while stabilizing all transmission queues. We first develop a centralized dynamic scheduling scheme with transmission strategy selection by using a stochastic network optimization approach.
To reduce the communication overhead, we then propose a distributed scheduling algorithm which only requires limited message exchange between the base stations. We also consider the impact of imperfect channel state information on the scheduling schemes and propose an efficient rate adjustment method to improve the performance for this case.
Simulation results show that the performance of the proposed distributed scheduling scheme is close to that of the centralized scheduling scheme, and both schemes achieve a better performance than schemes employing a single transmission strategy.
We formulate an optimization problem which aims to jointly select a user and the corresponding transmission strategy for each base station in order to maximize the overall system utility while stabilizing all transmission queues. We first develop a centralized dynamic scheduling scheme with transmission strategy selection by using a stochastic network optimization approach.
To reduce the communication overhead, we then propose a distributed scheduling algorithm which only requires limited message exchange between the base stations. We also consider the impact of imperfect channel state information on the scheduling schemes and propose an efficient rate adjustment method to improve the performance for this case.
Simulation results show that the performance of the proposed distributed scheduling scheme is close to that of the centralized scheduling scheme, and both schemes achieve a better performance than schemes employing a single transmission strategy.
Driver Fatigue Detection Using Machine Vision Approach
Driver fatigue plays a vital role in a large number of accidents. In this paper, a real time, machine vision-based system is proposed for the detection of driver fatigue which can detect the driver fatigue and can issue a warning early enough to avoid an accident.
Firstly, the face is located by machine vision based object detection algorithm, then eyes and eyebrows are detected and their count (four or less) is computed. By comparison of the calculated number of black spots, with a predefined value, which is four (Two eyes and two eye brows), for a particular time interval, driver fatigue can be detected and a timely warning can be issued whenever there will be symptoms of fatigue. The main advantage of this system is its fast processing time and very simple equipment.
This system runs at about 15 frames per second with a resolution of 320*240 pixels. This algorithm is implemented using MATLAB platform along with camera and is well suited for real world driving conditions since it can be non-intrusive by using a video camera to detect changes.
Firstly, the face is located by machine vision based object detection algorithm, then eyes and eyebrows are detected and their count (four or less) is computed. By comparison of the calculated number of black spots, with a predefined value, which is four (Two eyes and two eye brows), for a particular time interval, driver fatigue can be detected and a timely warning can be issued whenever there will be symptoms of fatigue. The main advantage of this system is its fast processing time and very simple equipment.
This system runs at about 15 frames per second with a resolution of 320*240 pixels. This algorithm is implemented using MATLAB platform along with camera and is well suited for real world driving conditions since it can be non-intrusive by using a video camera to detect changes.
Dynamic Ultrasonic Hybrid Localization System for Indoor Mobile Robots
An accurate dynamic ultrasonic hybrid localization system is presented for autonomous navigation of indoor mobile robots using multiple ultrasonic distance measurements and an extended Kalman filter (EKF). The ultrasonic sensor subsystem is composed of several ultrasonic transmitters (Txs) attached to the ceiling at known positions and several ultrasonic receivers equilaterally located on the top of the mobile robot, which has a moving speed that is not negligible.
An EKF-based algorithm with a state/observation vector composed of the robot pose (or the position and the orientation) is presented using odometric and ultrasonic distance measurements.
A dynamic distance estimation method is proposed to track the estimates of ultrasonic distance information from available Txs of interest using both odometric information from the robot and actual ultrasonic distance measurements.
This continuous dynamic distance estimation allows persistent use of the hybrid self-localization algorithm to accurately determine the pose of the robot. The experimental results with various trajectories clearly show that the proposed method is much more accurate than only the hybrid self-localization algorithm (without the dynamic distance estimation method).
An EKF-based algorithm with a state/observation vector composed of the robot pose (or the position and the orientation) is presented using odometric and ultrasonic distance measurements.
A dynamic distance estimation method is proposed to track the estimates of ultrasonic distance information from available Txs of interest using both odometric information from the robot and actual ultrasonic distance measurements.
This continuous dynamic distance estimation allows persistent use of the hybrid self-localization algorithm to accurately determine the pose of the robot. The experimental results with various trajectories clearly show that the proposed method is much more accurate than only the hybrid self-localization algorithm (without the dynamic distance estimation method).
Dynamic Wireless Sensor Networks for Real Time Safeguard of Workers Exposed to Physical Agents in Constructions Sites
The paper introduces a wireless sensor network platform specifically designed for the protection of workers employed in the building sector, exposed to critical physical agents, typical of their working scenario.
The network configuration makes use of either a standard ZigBee communication scheme, or a more versatile ad-hoc set-up, which narrows the necessary transmission bandwidth and lowers the frequency of the carriers. The relevant part of the research activity has been concentrated on the design and realization of a compact, wearable, washable, ergonomic, low cost wireless sensor node, suitable to detect a huge variety of physical phenomena.
The sample proposed in the paper has been specifically developed to measure two different kinds of exposure, UltraViolet rays and dust. Both these agents, for different reasons, represent a critical factors and a certified source of possible diseases.
The sensor node is embedded on the worker garment: the electronic components are sewed on the cloth, and the antenna is integrated within the fabric, and, together with the fabric, forms a unique structure. Preliminary results, obtained with a non-optimized and non-compact node, testify the validity of the approach and its applicability to real cases.
The network configuration makes use of either a standard ZigBee communication scheme, or a more versatile ad-hoc set-up, which narrows the necessary transmission bandwidth and lowers the frequency of the carriers. The relevant part of the research activity has been concentrated on the design and realization of a compact, wearable, washable, ergonomic, low cost wireless sensor node, suitable to detect a huge variety of physical phenomena.
The sample proposed in the paper has been specifically developed to measure two different kinds of exposure, UltraViolet rays and dust. Both these agents, for different reasons, represent a critical factors and a certified source of possible diseases.
The sensor node is embedded on the worker garment: the electronic components are sewed on the cloth, and the antenna is integrated within the fabric, and, together with the fabric, forms a unique structure. Preliminary results, obtained with a non-optimized and non-compact node, testify the validity of the approach and its applicability to real cases.
Efficient Traffic State Estimation for Large-Scale Urban Road Networks
This paper presents a systematic solution to efficiently estimate the traffic state of large-scale urban road networks. We first propose the new approach to construct the exact GIS-T digital map. The exact digital map can lay the solid foundation for the traffic state estimation with the data from Global Positioning System (GPS) probe vehicles.
Then, we present the following two effective methods based on GPS probe vehicles for the traffic state estimation: (1) the curve-fitting-based method and (2) the vehicle-tracking-based method. Finally, we test the proposed solution with a large number of real data from GPS probe vehicles and the standard digital map of Shanghai, China. In the experiments, data from thousands of GPS-equipped taxies were taken as the probe vehicles.
The estimation accuracy and operation speed of the two different methods were systematically measured and compared. In addition, the coverages of the GPS sampling points were also investigated for the large-scale urban road network in the spatial and temporal domains.
For the accuracy experiment, the ground truth was obtained by repeating the videos that were recorded on 24 road sections in downtown Shanghai. The experimental results illustrate that the proposed methods are effective and efficient in monitoring the traffic state of large-scale urban road networks.
Then, we present the following two effective methods based on GPS probe vehicles for the traffic state estimation: (1) the curve-fitting-based method and (2) the vehicle-tracking-based method. Finally, we test the proposed solution with a large number of real data from GPS probe vehicles and the standard digital map of Shanghai, China. In the experiments, data from thousands of GPS-equipped taxies were taken as the probe vehicles.
The estimation accuracy and operation speed of the two different methods were systematically measured and compared. In addition, the coverages of the GPS sampling points were also investigated for the large-scale urban road network in the spatial and temporal domains.
For the accuracy experiment, the ground truth was obtained by repeating the videos that were recorded on 24 road sections in downtown Shanghai. The experimental results illustrate that the proposed methods are effective and efficient in monitoring the traffic state of large-scale urban road networks.
Electric Vehicle Charging Method for Smart Homes/Buildings with a Photovoltaic System
Due to the increased penetration of electric vehicles (EVs) and photovoltaic (PV) systems, additional application for home/building energy management system (EMS) is needed to determine when and how much to charge an electric vehicle in an individual home/building.
This paper presents a smart EV charging method for smart homes/buildings with a PV system. The paper consists of two parts: EV charging scheduling algorithm for smart homes/buildings and implementation of prototype application for home/building EMS.
The proposed EV charging algorithm is designed to determine the optimal schedules of EV charging based on predicted PV output and electricity consumption. The implemented prototype application for home/building EMS can provide EV charging schedules according to user preferences. Numerical results are provided to demonstrate the effectiveness of the proposed smart EV charging method.
This paper presents a smart EV charging method for smart homes/buildings with a PV system. The paper consists of two parts: EV charging scheduling algorithm for smart homes/buildings and implementation of prototype application for home/building EMS.
The proposed EV charging algorithm is designed to determine the optimal schedules of EV charging based on predicted PV output and electricity consumption. The implemented prototype application for home/building EMS can provide EV charging schedules according to user preferences. Numerical results are provided to demonstrate the effectiveness of the proposed smart EV charging method.
Electromechanical Energy Scavenging from Current-Carrying Conductors
This paper describes a novel method for scavenging energy for electric power systems sensing applications by the use of permanent magnets that couple to the magnetic field generated by an alternating current flowing through a nearby conductor. The resulting mechanical energy is converted to electrical energy using piezoelectric transduction.
This electromechanical AC energy scavenging method is an attractive alternative to coil-based AC energy scavengers in cases where the scavengers cannot encircle the conductor. In such cases, the electromechanical AC energy scavenger has the potential to produce significantly more power than comparable coil-based methods.
The components of an electromechanical AC energy scavenger are described in detail, and experimental data from prototypes that are fabricated and tested in our laboratory are shown. The 20 cm3 prototypes generated up to 2.7 mW of power each from 20 A of nearby current. Theoretical power densities of electromechanical AC energy scavengers are compared to the power densities of representative coil-based methods, showing that in some cases the electromechanical AC scavengers can generate an order-of-magnitude more power than coil-based AC scavengers.
This paper demonstrates that electromechanical AC energy scavenging is a potential method for powering small size low cost stick-on wireless sensor networks.
This electromechanical AC energy scavenging method is an attractive alternative to coil-based AC energy scavengers in cases where the scavengers cannot encircle the conductor. In such cases, the electromechanical AC energy scavenger has the potential to produce significantly more power than comparable coil-based methods.
The components of an electromechanical AC energy scavenger are described in detail, and experimental data from prototypes that are fabricated and tested in our laboratory are shown. The 20 cm3 prototypes generated up to 2.7 mW of power each from 20 A of nearby current. Theoretical power densities of electromechanical AC energy scavengers are compared to the power densities of representative coil-based methods, showing that in some cases the electromechanical AC scavengers can generate an order-of-magnitude more power than coil-based AC scavengers.
This paper demonstrates that electromechanical AC energy scavenging is a potential method for powering small size low cost stick-on wireless sensor networks.
Electromyography Based Locomotion Pattern Recognition and Personal Positioning Toward Improved Context-Awareness Applications
Personal positioning has been playing an important role in context awareness and navigation. Pedestrian dead reckoning (PDR) solution is a positioning technology used where the global positioning system (GPS) signal is not available or its signal is mightily attenuated or reflected by constructions nearby, such as inside the buildings or in GPS degraded areas such as urban city, basement.
A traditional PDR solution employs a multisensor unit (integrating accelerometer, gyroscope, digital compass, barometer, etc.) to detect step occurrences, as well as to estimate the stride length. In our pilot research, we proposed a novel electromyography (EMG)-based method to fulfill that task and obtained satisfying PDR results.
In this paper, a further attempt is made to investigate the feasibility of using EMG sensors in sensing muscle activities to detect the corresponding locomotion patterns, and as a result, a new approach, which recognizes different locomotion patterns using EMG signals and constructs stride length models according to the recognition results, is then proposed to improve the positioning accuracy and robustness of the EMG-based PDR solution by adapting the stride length model into different locomotion patterns.
The experimental results demonstrate that EMG-based pattern recognition of four motions (walking, running, walking upstairs, walking downstairs) achieve an error rate of less than 2%. Combined with locomotion pattern recognition, the proposed EMG-based PDR solution yield a position deviation of less than 5 m within the whole distance of 404 m in a simulated indoor/outdoor field test. The proposed method is proven to be effective and practical in sensing context information, including both the userhbox{'}s activities and locations
A traditional PDR solution employs a multisensor unit (integrating accelerometer, gyroscope, digital compass, barometer, etc.) to detect step occurrences, as well as to estimate the stride length. In our pilot research, we proposed a novel electromyography (EMG)-based method to fulfill that task and obtained satisfying PDR results.
In this paper, a further attempt is made to investigate the feasibility of using EMG sensors in sensing muscle activities to detect the corresponding locomotion patterns, and as a result, a new approach, which recognizes different locomotion patterns using EMG signals and constructs stride length models according to the recognition results, is then proposed to improve the positioning accuracy and robustness of the EMG-based PDR solution by adapting the stride length model into different locomotion patterns.
The experimental results demonstrate that EMG-based pattern recognition of four motions (walking, running, walking upstairs, walking downstairs) achieve an error rate of less than 2%. Combined with locomotion pattern recognition, the proposed EMG-based PDR solution yield a position deviation of less than 5 m within the whole distance of 404 m in a simulated indoor/outdoor field test. The proposed method is proven to be effective and practical in sensing context information, including both the userhbox{'}s activities and locations
Embedded Flexible Force Sensor for In-Situ Tire–Road Interaction Measurements
In-situ sensing the tire-road interactions such as local contact friction force distributions provides crucial information for building accurate friction force models for vehicle safety control. In this paper, we report the development of an embedded, flexible local force sensor for measuring the tire local friction forces and their distributions.
A new pressure-sensitive, electric conductive rubber (PSECR) sensor is used and embedded inside the tire rubber layer to extract the multi-dimensional local friction forces on the tire contact patch. The low-cost, flexible PSECR sensor is oriented in certain directions, and is sensitive to multiple compressive forces.
To interpret the sensor measurements, we use a beam-spring model for the tire-road interactions to extract the local contact friction forces. The experimental results of stick-slip interaction testing on a motorcycle tire demonstrate the effective and good performance of the PSECR-based tire force sensor.
A new pressure-sensitive, electric conductive rubber (PSECR) sensor is used and embedded inside the tire rubber layer to extract the multi-dimensional local friction forces on the tire contact patch. The low-cost, flexible PSECR sensor is oriented in certain directions, and is sensitive to multiple compressive forces.
To interpret the sensor measurements, we use a beam-spring model for the tire-road interactions to extract the local contact friction forces. The experimental results of stick-slip interaction testing on a motorcycle tire demonstrate the effective and good performance of the PSECR-based tire force sensor.
Embedded system integrated into a wireless sensor network for online dynamic Torque and efficiency monitoring in Induction Motors
The system proposed in this paper aims at monitoring the torque and efficiency in induction motors in real time by employing wireless sensor networks (WSNs). An embedded system is employed for acquiring electrical signals from the motor in a noninvasive manner, and then performing local processing for torque and efficiency estimation.
The values calculated by the embedded system are transmitted to a monitoring unit through an IEEE 802.15.4-based WSN. At the base unit, various motors can be monitored in real time. An experimental study was conducted for observing the relationship between the WSN performance and the spectral occupancy at the operating environment.
This study demonstrated that the use of intelligent nodes, with local processing capability, is essential for this type of application. The embedded system was deployed on a workbench, and studies were conducted to analyze torque and system efficiency.
The values calculated by the embedded system are transmitted to a monitoring unit through an IEEE 802.15.4-based WSN. At the base unit, various motors can be monitored in real time. An experimental study was conducted for observing the relationship between the WSN performance and the spectral occupancy at the operating environment.
This study demonstrated that the use of intelligent nodes, with local processing capability, is essential for this type of application. The embedded system was deployed on a workbench, and studies were conducted to analyze torque and system efficiency.
Emergency Management of Urban Rail Transportation based on Parallel Systems
Integrating artificial systems, computational experiments, and parallel execution (ACP) is an effective approach to modeling, simulating, and intervening real complex systems. Emergency response is an important issue in the operation of urban rail transport systems for ensuring the safety of people and property. Inspired by the ACP method, this paper introduces a basic framework of parallel control and management (PCM) for emergency response of urban rail transportation systems.
The proposed framework is elaborated from three interdependent aspects: Points, Lines, and Networks. Points represent the modeling of urban rail stations, Lines describe the microscopic characteristics of urban rail connections between designated stations, and Networks present the macroscopic properties of all the urban rail connections.
Based on the given framework, a series of parallel experiments, which were impossible to achieve in real systems, can now be conducted in the constructed artificial system.
Furthermore, the constructed artificial system can be used to test and develop effective emergency control and management strategies for real rail transport systems. Therefore, this proposed framework will be able to enhance the reliability, security, robustness, and maneuverability of urban rail transport systems in case of an emergency.
The proposed framework is elaborated from three interdependent aspects: Points, Lines, and Networks. Points represent the modeling of urban rail stations, Lines describe the microscopic characteristics of urban rail connections between designated stations, and Networks present the macroscopic properties of all the urban rail connections.
Based on the given framework, a series of parallel experiments, which were impossible to achieve in real systems, can now be conducted in the constructed artificial system.
Furthermore, the constructed artificial system can be used to test and develop effective emergency control and management strategies for real rail transport systems. Therefore, this proposed framework will be able to enhance the reliability, security, robustness, and maneuverability of urban rail transport systems in case of an emergency.
Energy management in an automated Solar powered irrigation system
The projected population of India being 1500 million by 2050 and agriculture remaining as the primary source of livelihood in rural areas, the focus should be on the increase of productivity.
Though our country claims to have developed in terms of science and technology, erratic power supply or complete breakdown for hours together has almost become routine today. Solar power is being increasingly utilized worldwide as a renewable source of energy. India has huge untapped solar off-grid opportunities. This paper gives information about development procedure of an embedded system for Off-Grid irrigation system.
The design projects on developing an intelligent controlled mechanism for best possible utilization of resources for irrigation. The farmer (user) can water the fields from any place using GSM technique which provides an acknowledgement message about the job status.
The main advantage of this project is optimizing the power usage through water resource management and also saving government's free subsidiary electricity. This proves an efficient and economy way of irrigation and this will automate the agriculture sector.
Though our country claims to have developed in terms of science and technology, erratic power supply or complete breakdown for hours together has almost become routine today. Solar power is being increasingly utilized worldwide as a renewable source of energy. India has huge untapped solar off-grid opportunities. This paper gives information about development procedure of an embedded system for Off-Grid irrigation system.
The design projects on developing an intelligent controlled mechanism for best possible utilization of resources for irrigation. The farmer (user) can water the fields from any place using GSM technique which provides an acknowledgement message about the job status.
The main advantage of this project is optimizing the power usage through water resource management and also saving government's free subsidiary electricity. This proves an efficient and economy way of irrigation and this will automate the agriculture sector.
Energy Reduction in a Pallet-Constrained Flow Shop Through On–Off Control of Idle Machines
For flexible manufacturing systems, there are normally some durations in which a number of machines are idle and do not process any parts. Devising a control policy to turn off the idle machines and reduce their level of energy consumption is a significant contribution towards the green manufacturing paradigm.
This paper addresses the design of such a control strategy for a closed-loop flow shop plant based on a one-loop pallet system. The main goal is to coordinate running of the machines and motion of pallets to gain the minimal energy consumption in idle machines, as well as to obtain the desired throughput for the plant. To fulfill this goal, first mathematical conditions, which economically characterize the on-off control for machines, are presented.
Constrained to these conditions and the mathematical models describing the pallet system, a mixed integer nonlinear minimization problem with the energy monitor as the objective function is then developed. Provided that the problem computation time can be managed, the optimal control for the operation of the plant and the minimal energy consumption in the idle machines are computed.
To deal with the time complexity, a linearized form of the model and a heuristic approach are introduced. These methods are applied to some examples of industrial size, and their impacts in practice are discussed and verified by using a discrete event simulation tool.
This paper addresses the design of such a control strategy for a closed-loop flow shop plant based on a one-loop pallet system. The main goal is to coordinate running of the machines and motion of pallets to gain the minimal energy consumption in idle machines, as well as to obtain the desired throughput for the plant. To fulfill this goal, first mathematical conditions, which economically characterize the on-off control for machines, are presented.
Constrained to these conditions and the mathematical models describing the pallet system, a mixed integer nonlinear minimization problem with the energy monitor as the objective function is then developed. Provided that the problem computation time can be managed, the optimal control for the operation of the plant and the minimal energy consumption in the idle machines are computed.
To deal with the time complexity, a linearized form of the model and a heuristic approach are introduced. These methods are applied to some examples of industrial size, and their impacts in practice are discussed and verified by using a discrete event simulation tool.
Energy Saving Opportunity Analysis of Automotive Serial Production Systems
Conventionally, improving production efficiency, flexibility and responsiveness has been the primary research focus of production management, while energy consumption has received relatively little attention. Energy consumption plays a more and more important role in the manufacturing environment.
This is mainly driven by energy cost and environmental concerns. When the energy system becomes complicated and coupled with ongoing production, it is very difficult to hunt the “hidden treasure” which affects the overall benefit of a manufacturing system.
This paper provides a systematic method to search for energy saving opportunities and strategies. We start from dynamic production transient analysis and provide quantitative analysis for identifying energy saving opportunity in a system.
Furthermore, energy saving strategy is justified through cost analysis for tradeoffs between energy savings and throughput loss. A case study is conducted to demonstrate its potential on energy savings in a multistage manufacturing system.
This is mainly driven by energy cost and environmental concerns. When the energy system becomes complicated and coupled with ongoing production, it is very difficult to hunt the “hidden treasure” which affects the overall benefit of a manufacturing system.
This paper provides a systematic method to search for energy saving opportunities and strategies. We start from dynamic production transient analysis and provide quantitative analysis for identifying energy saving opportunity in a system.
Furthermore, energy saving strategy is justified through cost analysis for tradeoffs between energy savings and throughput loss. A case study is conducted to demonstrate its potential on energy savings in a multistage manufacturing system.
Energy-Efficient Production Systems through Schedule-Based Operations
Control of production operations is considered as one of the most economical methods to improve energy efficiency in manufacturing systems. This paper investigates energy consumption reduction in production systems through effective scheduling of machine startup and shutdown.
Specifically, we consider serial production lines with finite buffers and machines having Bernoulli reliability model. This machine reliability model is applicable in production situations, where the downtime is relatively short and comparable to machine cycle time (e.g., automotive paint shops and general assembly). In this paper, using transient analysis of the systems at hand, an analytical performance evaluation technique is developed for Bernoulli serial lines with time-dependent machine efficiencies.
In addition, tradeoff between productivity and energy-efficiency in production systems is discussed and the energy-efficient production problem is formulated as a constrained optimization problem. The effects and practical implications of operations schedule are demonstrated using a numerical study on automotive paint shop operations. Note to Practitioners - This paper develops an effective analytical tool to evaluate the performance of production systems with time-varying parameters of machine reliability.
Using this tool, production engineers and managers can predict the performance of the production systems in real-time with high accuracy. In addition, based on this tool, production operators can determine the machine startup and shutdown schedule based on the current status of the line and production requirement. Numerical experiments show that significant energy savings can be obtained by applying effective machine operations schedule.
Specifically, we consider serial production lines with finite buffers and machines having Bernoulli reliability model. This machine reliability model is applicable in production situations, where the downtime is relatively short and comparable to machine cycle time (e.g., automotive paint shops and general assembly). In this paper, using transient analysis of the systems at hand, an analytical performance evaluation technique is developed for Bernoulli serial lines with time-dependent machine efficiencies.
In addition, tradeoff between productivity and energy-efficiency in production systems is discussed and the energy-efficient production problem is formulated as a constrained optimization problem. The effects and practical implications of operations schedule are demonstrated using a numerical study on automotive paint shop operations. Note to Practitioners - This paper develops an effective analytical tool to evaluate the performance of production systems with time-varying parameters of machine reliability.
Using this tool, production engineers and managers can predict the performance of the production systems in real-time with high accuracy. In addition, based on this tool, production operators can determine the machine startup and shutdown schedule based on the current status of the line and production requirement. Numerical experiments show that significant energy savings can be obtained by applying effective machine operations schedule.
Ethernet Enabled Digital I/0 Control in Embedded Systems
This paper presents very simple and economical way to provide Ethernet connectivity to microcontroller based embedded systems. This system uses ATmega328p microcontroller to store the main application source code, web pages and TCP/IP stack which is a vital element of the system software.
An Ethernet controller chip, ENC 28J60 is used to handle the Ethernet communications and is interfaced with the host microcontroller using SPI pins. There are several I/O pins available at the microcontroller which are used to interface with sensors and relays for monitoring and controlling operations.
Nowadays, Internet has spread worldwide and most of the internet connections use Ethernet as media for data transfer. In industries or in home appliances, most of the time we need to monitor and control different parameters using microcontrollers. Once we enable Ethernet interface to such systems, we can communicate with them remotely over the internet.
An Ethernet controller chip, ENC 28J60 is used to handle the Ethernet communications and is interfaced with the host microcontroller using SPI pins. There are several I/O pins available at the microcontroller which are used to interface with sensors and relays for monitoring and controlling operations.
Nowadays, Internet has spread worldwide and most of the internet connections use Ethernet as media for data transfer. In industries or in home appliances, most of the time we need to monitor and control different parameters using microcontrollers. Once we enable Ethernet interface to such systems, we can communicate with them remotely over the internet.
EVANS 3: Home appliance control system with appliance authentication framework using Augmented Reality technology
The popularity of home appliances continues to increase that can interconnect with other appliances through networks. For users who want to identify the network home appliances they want to operate, their operation is complex and difficult since their locations are not represented within the operating system.
We propose Embodied Visualization with Augmented Reality for Networked System 3 (EVANS 3) to solve operation problems with obvious and intuitive controls by implementing augmented reality (AR) technology.
We implemented our proposed LED Marker instead of the use of graphical images (image markers) as the AR markers to identify the network home appliance's location at any distant and altering light environments. By dynamically operating LED Markers, we can achieve a comfortable and effective appliance authentication environment for suitable operating conditions
We propose Embodied Visualization with Augmented Reality for Networked System 3 (EVANS 3) to solve operation problems with obvious and intuitive controls by implementing augmented reality (AR) technology.
We implemented our proposed LED Marker instead of the use of graphical images (image markers) as the AR markers to identify the network home appliance's location at any distant and altering light environments. By dynamically operating LED Markers, we can achieve a comfortable and effective appliance authentication environment for suitable operating conditions
Expanding Gate Level Information Flow Tracking for Multilevel Security
Embedded systems found in critical infrastructures require tight information flow controls to prevent unintended interference between different system components. These critical systems require extensive testing and verification to ensure strict enforcement of information flow policy.
To assist in this process, gate level information flow tracking (GLIFT) has been proposed to expose all flows of information through Boolean gates. However, the current work in this realm only considers a two-level security lattice (LOW ? HIGH).
In this letter, we expand the GLIFT method to multilevel security lattices and provide an analysis of the overheads using IWLS benchmarks. Results show that expanding GLIFT to multilevel security lattices produces overheads and we discuss potential research on its applications.
To assist in this process, gate level information flow tracking (GLIFT) has been proposed to expose all flows of information through Boolean gates. However, the current work in this realm only considers a two-level security lattice (LOW ? HIGH).
In this letter, we expand the GLIFT method to multilevel security lattices and provide an analysis of the overheads using IWLS benchmarks. Results show that expanding GLIFT to multilevel security lattices produces overheads and we discuss potential research on its applications.
Experimental Analysis of Laser Interferometry based Robust Motion Tracking Control of a Flexure-Based Mechanism
This paper presents experimental analysis of laser interferometry-based closed-loop robust motion tracking control for flexure-based four-bar micro/nano manipulator. To enhance the accuracy of micro/nano manipulation, laser interferometry realized robust motion tracking control is established with the experimental facility.
This paper contains brief discussions about the error sources associated with the laser interferometry-based sensing and measurement technique, along with detailed error analysis and estimation. Comparative error analysis of capacitive position sensor-based system and laser interferometry-based system is also presented. Robust control demonstrates high precision and accurate motion tracking of the four-bar flexure-based mechanism.
The experimental results demonstrate precise motion tracking, where resultant closed-loop position tracking error is of the order of ± 20 nm, and a steady-state error of about ±10 nm. With the experimental study and error analysis, we offer evidence that the laser interferometry-based closed-loop robust motion tracking control can minimize positioning and tracking errors during dynamic motion.
This paper contains brief discussions about the error sources associated with the laser interferometry-based sensing and measurement technique, along with detailed error analysis and estimation. Comparative error analysis of capacitive position sensor-based system and laser interferometry-based system is also presented. Robust control demonstrates high precision and accurate motion tracking of the four-bar flexure-based mechanism.
The experimental results demonstrate precise motion tracking, where resultant closed-loop position tracking error is of the order of ± 20 nm, and a steady-state error of about ±10 nm. With the experimental study and error analysis, we offer evidence that the laser interferometry-based closed-loop robust motion tracking control can minimize positioning and tracking errors during dynamic motion.
Experimental Investigation of the Roles of Blood Volume and Density in Finger Photoplethysmography
Using simultaneous photoplethysmogram (PPG) and pulse transducer signals from the same finger, a high correlation (Mean: 98.6, STD: 1) is obtained between the AC part of the PPG and estimated volume changes (after normalization). These results point to the fact that in the resting fingertip, PPG signal variations are only due to volume changes and that blood density does not change thus has no contribution.
Experimental Study and Design of Smart Energy Meter for the Smart Grid
The demand for energy is increasing as a result of the growth in both population and industrial development. To improve the energy efficiency, consumers need to be more aware of their energy consumption. In recent years, utilities have started developing new electric energy meters which are known as smart meters.
A smart meter is a digital energy meter that measures the consumption of electrical energy and provides other additional information as compared to the traditional energy meter. The aim is to provide the consumer and supplier an easy way to monitor the energy. Smart meters are considered a key component of the smart grid as these will allow more interactivity between the consumers and the provider.
Smart meters will enable two-way and real-time communication between the consumers and the provider. Considering the increase of electricity demand in Saudi Arabia, smart meters can decrease the overall energy consumption.
This paper presents the development of a GSM and ZigBee based smart meter. This meter can measure the energy and send the information to the service provider, who can store this information and notify the consumer through SMS messages or through the internet.
A smart meter is a digital energy meter that measures the consumption of electrical energy and provides other additional information as compared to the traditional energy meter. The aim is to provide the consumer and supplier an easy way to monitor the energy. Smart meters are considered a key component of the smart grid as these will allow more interactivity between the consumers and the provider.
Smart meters will enable two-way and real-time communication between the consumers and the provider. Considering the increase of electricity demand in Saudi Arabia, smart meters can decrease the overall energy consumption.
This paper presents the development of a GSM and ZigBee based smart meter. This meter can measure the energy and send the information to the service provider, who can store this information and notify the consumer through SMS messages or through the internet.
Experimental Study on the Atmospheric Delay based on GPS, SAR Interferometry and Numerical Weather Model Data
In this paper, we present the results of an experiment aiming to compare measurements of atmospheric delay by synthetic aperture radar (SAR) interferometry and GPS techniques to estimates by numerical weather prediction.
Maps of the differential atmospheric delay are generated by processing a set of interferometric SAR images acquired by the ENVISAT-ASAR mission over the Lisbon region from April to November 2009. GPS measurements of the wet zenith delay are carried out over the same area, covering the time interval between the first and the last SAR acquisition.
The Weather Research and Forecasting (WRF) model is used to model the atmospheric delay over the study area at about the same time of SAR acquisitions. The analysis of results gives hints to devise mitigation approaches of atmospheric artifacts in SAR interferometry applications.
Maps of the differential atmospheric delay are generated by processing a set of interferometric SAR images acquired by the ENVISAT-ASAR mission over the Lisbon region from April to November 2009. GPS measurements of the wet zenith delay are carried out over the same area, covering the time interval between the first and the last SAR acquisition.
The Weather Research and Forecasting (WRF) model is used to model the atmospheric delay over the study area at about the same time of SAR acquisitions. The analysis of results gives hints to devise mitigation approaches of atmospheric artifacts in SAR interferometry applications.
Fabrication and Characterization of Micromachined Piezoelectric T-Beam Actuators
This paper presents a monolithically fabricated microelectromechanical piezoelectric cantilever beam with a T-shaped cross section capable of in-plane and out-of-plane displacements and sensing. High-aspect-ratio T-beams are achieved by direct micromachining of bulk lead zirconate titanate (PZT-4) via reactive ion etching of 65- µm-deep features.
Electrodes deposited on the top and bottom web and flange regions of the T-shaped structure allow in-plane and out-of-plane motion actuation and sensing. The T-beam structures were tested for in-plane and out-of-plane tip displacements, out-of-plane blocking force, and impedance response.
These results are explained using analytical models that predict static deflection, blocking force, and resonance frequency. Nine prototype micromachined T-beams are fabricated that achieve up to 129 µm of out-of-plane displacement, 11.6 µm of in-plane displacement, and 700 µN of out-of-plane blocking force.
Electrodes deposited on the top and bottom web and flange regions of the T-shaped structure allow in-plane and out-of-plane motion actuation and sensing. The T-beam structures were tested for in-plane and out-of-plane tip displacements, out-of-plane blocking force, and impedance response.
These results are explained using analytical models that predict static deflection, blocking force, and resonance frequency. Nine prototype micromachined T-beams are fabricated that achieve up to 129 µm of out-of-plane displacement, 11.6 µm of in-plane displacement, and 700 µN of out-of-plane blocking force.
Fall Detection by built-In Tri axes Accelerometer On Smartphone
In this study, a fall detection system based on the data acquired from a waist-mounted smartphone has been developed in a real-time environment. The built-in tri-accelerometer was utilized to collect the information about body movement. At the same time, the smartphone is able to classify the data for activity recognition.
Body motion can be classified into five different patterns, i.e. vertical activity, lying, sitting or static standing, horizontal activity and fall. If a fall is suspected, an automatic Multimedia Messaging Service (MMS) will be sent to pre-selected people, with information including the time, GPS coordinate, and Google map of suspected fall location.
The major advantage of the proposed system is the use of smartphone which is readily available to most people.
Body motion can be classified into five different patterns, i.e. vertical activity, lying, sitting or static standing, horizontal activity and fall. If a fall is suspected, an automatic Multimedia Messaging Service (MMS) will be sent to pre-selected people, with information including the time, GPS coordinate, and Google map of suspected fall location.
The major advantage of the proposed system is the use of smartphone which is readily available to most people.
Fault Detection by Labeled Petri Nets in Centralized and Distributed Approaches
This paper addresses the problem of online fault detection and diagnosis in discrete event systems modeled by labeled Petri nets and using Integer Linear Programming Problem (ILPP) solutions. In particular, unobservable (silent) transitions model faults and both observable and unobservable transitions model the nominal system behavior. Furthermore, observable transitions exhibit a kind of non determinism since several different transitions may share the same event label.
This paper proposes two diagnosers that work in two different system settings. The first one is a centralized fault detection strategy: the diagnoser waits for an observable event and an algorithm defines and solves some ILPPs to decide whether the system behavior is normal or may exhibit some faults.
In the second setting, the system consists of a set of interacting PN modules and each module is monitored by a diagnoser that has local information on the module structure. Moreover, each diagnoser observes and detects the faults of the module it is attached to and shares information in some of its places that are shared with other modules of the system. Some case studies show the two different approaches and point out the peculiarities of the proposed strategies.
This paper proposes two diagnosers that work in two different system settings. The first one is a centralized fault detection strategy: the diagnoser waits for an observable event and an algorithm defines and solves some ILPPs to decide whether the system behavior is normal or may exhibit some faults.
In the second setting, the system consists of a set of interacting PN modules and each module is monitored by a diagnoser that has local information on the module structure. Moreover, each diagnoser observes and detects the faults of the module it is attached to and shares information in some of its places that are shared with other modules of the system. Some case studies show the two different approaches and point out the peculiarities of the proposed strategies.
Fault Diagnosis using an Enhanced Relevance Vector Machine (RVM) for Partially Diagnosable Multi-station Assembly Processes
Dimensional integrity has a significant impact on the quality of the final products in multistation assembly processes. A large body of research work in fault diagnosis has been proposed to identify the root causes of the large dimensional variations on products.
These methods are based on a linear relationship between the dimensional measurements of the products and the possible process errors, and assume that the number of measurements is greater than that of process errors. However, in practice, the number of measurements is often less than that of process errors due to economical considerations.
This brings a substantial challenge to the fault diagnosis in multistation assembly processes since the problem becomes solving an underdetermined system. In order to tackle this challenge, a fault diagnosis methodology is proposed by integrating the state space model with the enhanced relevance vector machine (RVM) to identify the process faults through the sparse estimate of the variance change of the process errors. The results of case studies demonstrate that the proposed methodology can identify process faults successfully.
These methods are based on a linear relationship between the dimensional measurements of the products and the possible process errors, and assume that the number of measurements is greater than that of process errors. However, in practice, the number of measurements is often less than that of process errors due to economical considerations.
This brings a substantial challenge to the fault diagnosis in multistation assembly processes since the problem becomes solving an underdetermined system. In order to tackle this challenge, a fault diagnosis methodology is proposed by integrating the state space model with the enhanced relevance vector machine (RVM) to identify the process faults through the sparse estimate of the variance change of the process errors. The results of case studies demonstrate that the proposed methodology can identify process faults successfully.
Field variables Monitoring in real time (GPS, Soil, Temperature) with precision Farming Application
A simple system has been developed to transmit field data in real time. This data consist in data of the Global Positioning System receiver (GPS), soil moisture and temperature. Individual locations are mapped to indicate the tracking for a GPS receiver.
Formal Methods for Early Analysis of Functional Reliability in Component-Based Embedded Applications
We present formal methods for determining whether a set of components with given reliability certificates for specific functional properties are adequate to guarantee desired end-to-end properties with specified reliability requirements. We introduce a formal notion for the reliability gap in component-based designs and demonstrate the proposed approach for analyzing this gap using a case study developed around an Elevator Control System.
Front Sensor and GPS-Based Lateral Control of Automated Vehicles
This work proposes an automated steering control system for passenger cars. Feasibility of a control strategy based on a front sensor and a Global Positioning System (GPS) has been evaluated using computer simulations.
First, the steering angles can be estimated by using the driving data provided by the front sensor and GPS. Second, the road curvature estimator for real-time situation is designed based on its relationship with the steering angle. Third, accurate and real-time estimation of the vehicle's lateral displacements with respect to the road is accomplished.
Finally, a closed-loop controller is used to control the lateral dynamics of the vehicle. The proposed estimation and control algorithms are validated by computer simulation results. They show that this lateral steering control system achieves good and robust performance for vehicles to follow a reference path.
First, the steering angles can be estimated by using the driving data provided by the front sensor and GPS. Second, the road curvature estimator for real-time situation is designed based on its relationship with the steering angle. Third, accurate and real-time estimation of the vehicle's lateral displacements with respect to the road is accomplished.
Finally, a closed-loop controller is used to control the lateral dynamics of the vehicle. The proposed estimation and control algorithms are validated by computer simulation results. They show that this lateral steering control system achieves good and robust performance for vehicles to follow a reference path.
Functional and Behavior Models for the Supervision of an Intelligent and Autonomous System
The graphical approaches often have different backgrounds and view a system or an algebraic model from different perspectives in order to facilitate the communication and the understanding.
These graphical approaches satisfy the modeling needs and give a clear and easily understandable overview of the behavioral and functional models and make easier to see what the process is, which vulnerabilities and asset that are involved and how the system works. The main goal of this paper is to develop and implement a methodology which combines the functional analysis and the bond graph (BG) tool for intelligent and autonomous systems.
As a result, a supervisory interface is obtained, given under a finite automaton, displaying to the operators the possibilities the system has to achieve or not, its objectives. Each operating mode, corresponding to a vertex of the automaton, is associated with a set of services from a functional point-of-view and is defined accurately by a behavioral BG model.
Furthermore, the service availability (associated to the BG elements) and the conditions for switching from one mode to another one are analyzed by fault detection and isolation algorithms generated on the basis of the structural and causal properties of the BG tool. Moreover, when a fault is not completely isolable some results can nevertheless be expressed in terms of available or unavailable services.
These graphical approaches satisfy the modeling needs and give a clear and easily understandable overview of the behavioral and functional models and make easier to see what the process is, which vulnerabilities and asset that are involved and how the system works. The main goal of this paper is to develop and implement a methodology which combines the functional analysis and the bond graph (BG) tool for intelligent and autonomous systems.
As a result, a supervisory interface is obtained, given under a finite automaton, displaying to the operators the possibilities the system has to achieve or not, its objectives. Each operating mode, corresponding to a vertex of the automaton, is associated with a set of services from a functional point-of-view and is defined accurately by a behavioral BG model.
Furthermore, the service availability (associated to the BG elements) and the conditions for switching from one mode to another one are analyzed by fault detection and isolation algorithms generated on the basis of the structural and causal properties of the BG tool. Moreover, when a fault is not completely isolable some results can nevertheless be expressed in terms of available or unavailable services.
Fuzzy Virtual Reference Model Sensorless Tracking Control for Linear Induction Motors
This paper introduces a fuzzy virtual reference model (FVRM) synthesis method for linear induction motor (LIM) speed sensorless tracking control. First, we represent the LIM as a Takagi-Sugeno fuzzy model. Second, we estimate the immeasurable mover speed and secondary flux by a fuzzy observer. Third, to convert the speed tracking control into a stabilization problem, we define the internal desired states for state tracking via an FVRM.
Finally, by solving a set of linear matrix inequalities (LMIs), we obtain the observer gains and the control gains where exponential convergence is guaranteed. The contributions of the approach in this paper are threefold: 1) simplified approach-speed tracking problem converted into stabilization problem; 2) omit need of actual reference model-FVRM generates internal desired states; and 3) unification of controller and observer design-control objectives are formulated into an LMI problem where powerful numerical toolboxes solve controller and observer gains. Finally, experiments are carried out to verify the theoretical results and show satisfactory performance both in transient response and robustness
Finally, by solving a set of linear matrix inequalities (LMIs), we obtain the observer gains and the control gains where exponential convergence is guaranteed. The contributions of the approach in this paper are threefold: 1) simplified approach-speed tracking problem converted into stabilization problem; 2) omit need of actual reference model-FVRM generates internal desired states; and 3) unification of controller and observer design-control objectives are formulated into an LMI problem where powerful numerical toolboxes solve controller and observer gains. Finally, experiments are carried out to verify the theoretical results and show satisfactory performance both in transient response and robustness
Gestures for industry Intuitive human-robot communication from human observation
Human-robot collaborative work has the potential to advance quality, efficiency and safety in manufacturing. In this paper we present a gestural communication lexicon for human-robot collaboration in industrial assembly tasks and establish methodology for producing such a lexicon.
Our user experiments are grounded in a study of industry needs, providing potential real-world applicability to our results. Actions required for industrial assembly tasks are abstracted into three classes: part acquisition, part manipulation, and part operations. We analyzed the communication between human pairs performing these subtasks and derived a set of communication terms and gestures.
We found that participant-provided gestures are intuitive and well suited to robotic implementation, but that interpretation is highly dependent on task context. We then implemented these gestures on a robot arm in a human-robot interaction context, and found the gestures to be easily interpreted by observers.
We found that observation of human-human interaction can be effective in determining what should be communicated in a given human-robot task, how communication gestures should be executed, and priorities for robotic system implementation based on frequency of use.
Our user experiments are grounded in a study of industry needs, providing potential real-world applicability to our results. Actions required for industrial assembly tasks are abstracted into three classes: part acquisition, part manipulation, and part operations. We analyzed the communication between human pairs performing these subtasks and derived a set of communication terms and gestures.
We found that participant-provided gestures are intuitive and well suited to robotic implementation, but that interpretation is highly dependent on task context. We then implemented these gestures on a robot arm in a human-robot interaction context, and found the gestures to be easily interpreted by observers.
We found that observation of human-human interaction can be effective in determining what should be communicated in a given human-robot task, how communication gestures should be executed, and priorities for robotic system implementation based on frequency of use.
Green Charge: Managing Renewable Energy in Smart Buildings
In this study, following market penetration of PHEVs and EVs, the types of green car need to be supplied electricity externally, the efficient power charging infrastructure with a suggested charging monitoring system considering the smart grid system is proposed. PHEVs and EVs of green cars are used with electric supplied from Smart-Grid and stored in batteries.
For the process, to establish stable and efficient connections between cars and the grids, the charging-monitoring system to manage electricity supply with communication information is required. The developed power supply system for charging automobiles are suitable for places such as 1:1 type or household usage.
However, for the places required to charge simultaneously many vehicles, such as corporate or public parking lots, the system has problems causing installation cost increase while taking certain amount of spaces as well as inconvenient to manage for electricity suppliers.
Therefore, in this study, we are proposed the efficient energy transformation method with the suggested charging monitoring system in grid, which has along with the description of charging process mechanism, the detail of control algorithm and the definition of function and interface between the relevant systems.
For the process, to establish stable and efficient connections between cars and the grids, the charging-monitoring system to manage electricity supply with communication information is required. The developed power supply system for charging automobiles are suitable for places such as 1:1 type or household usage.
However, for the places required to charge simultaneously many vehicles, such as corporate or public parking lots, the system has problems causing installation cost increase while taking certain amount of spaces as well as inconvenient to manage for electricity suppliers.
Therefore, in this study, we are proposed the efficient energy transformation method with the suggested charging monitoring system in grid, which has along with the description of charging process mechanism, the detail of control algorithm and the definition of function and interface between the relevant systems.
GSM based automatic energy meter reading system with instant billing
The technology of e-metering (Electronic Metering) has gone through rapid technological advancements and there is increased demand for a reliable and efficient Automatic Meter Reading (AMR) system. This paper presents the design of a simple low cost wireless GSM energy meter and its associated web interface, for automating billing and managing the collected data globally.
The proposed system replaces traditional meter reading methods and enables remote access of existing energy meter by the energy provider. Also they can monitor the meter readings regularly without the person visiting each house. A GSM based wireless communication module is integrated with electronic energy meter of each entity to have remote access over the usage of electricity. A PC with a GSM receiver at the other end, which contains the database acts as the billing point.
Live meter reading from the GSM enabled energy meter is sent back to this billing point periodically and these details are updated in a central database. A new interactive, user friendly graphical user interface is developed using Microsoft visual studio .NET framework and C#. With proper authentication, users can access the developed web page details from anywhere in the world. The complete monthly usage and due bill is messaged back to the customer after processing these data.
The proposed system replaces traditional meter reading methods and enables remote access of existing energy meter by the energy provider. Also they can monitor the meter readings regularly without the person visiting each house. A GSM based wireless communication module is integrated with electronic energy meter of each entity to have remote access over the usage of electricity. A PC with a GSM receiver at the other end, which contains the database acts as the billing point.
Live meter reading from the GSM enabled energy meter is sent back to this billing point periodically and these details are updated in a central database. A new interactive, user friendly graphical user interface is developed using Microsoft visual studio .NET framework and C#. With proper authentication, users can access the developed web page details from anywhere in the world. The complete monthly usage and due bill is messaged back to the customer after processing these data.
High detection performance of non Dispersive infrared CO2 sensor using stair-tapered reflector
In this paper, we propose tapered reflectors having stair-like structures that focus scattered infrared (IR) rays to enhance the detection performance of a non-dispersive IR (NDIR) ${rm CO}_{2}$ sensor. We demonstrate that the sensitivity of the output voltage is increased by 2 and 1.27 times in simulations and experiments, respectively, compared with the case when conventionally tapered reflectors are used.
Through applying a stair-like structure inside the tapered optical cavity, scattered IR rays are condensed, and more accurate ${rm CO}_{2}$ concentration measurements are possible. In addition, we show that the output voltage changes only slightly with temperature and humidity variations compared with the conventionally tapered optical cavity.
Because the proposed structure can be applied to any type of optical cavity without major modifications, we expect that it can resolve the performance limitations of low-end NDIR gas sensors.
Through applying a stair-like structure inside the tapered optical cavity, scattered IR rays are condensed, and more accurate ${rm CO}_{2}$ concentration measurements are possible. In addition, we show that the output voltage changes only slightly with temperature and humidity variations compared with the conventionally tapered optical cavity.
Because the proposed structure can be applied to any type of optical cavity without major modifications, we expect that it can resolve the performance limitations of low-end NDIR gas sensors.
High-Level Scheduling of Energy Optimal Trajectories
The reduction of energy consumption is today addressed with great effort in manufacturing industry. In this paper, we improve upon a previously presented method for robotic system scheduling. By applying dynamic programming to existing trajectories, we generate new energy optimal trajectories that follow the same path but in a different execution time frame.
With this new method, it is possible to solve the optimization problem for a range of execution times for the individual operations, based on one simulation only. The minimum energy trajectories can then be used to derive a globally energy optimal schedule.
A case study of a cell comprised of four six-link manipulators is presented, in which energy optimal dynamic time scaling is compared to linear time scaling. The results show that a significant decrease in energy consumption can be achieved for any given cycle time.
With this new method, it is possible to solve the optimization problem for a range of execution times for the individual operations, based on one simulation only. The minimum energy trajectories can then be used to derive a globally energy optimal schedule.
A case study of a cell comprised of four six-link manipulators is presented, in which energy optimal dynamic time scaling is compared to linear time scaling. The results show that a significant decrease in energy consumption can be achieved for any given cycle time.
High-Resolution Parameter Estimation Method to Identify Broken Rotor Bar Faults in Induction Motors
The classical multiple signal classification (MUSIC) method has been widely used in induction machine fault detection and diagnosis. This method can extract meaningful frequencies but cannot give accurate amplitude information of fault harmonics. In this paper, we propose a new frequency analysis of stator current to estimate fault-sensitive frequencies and their amplitudes for broken rotor bars (BRBs).
The proposed method employs a frequency estimator, an amplitude estimator, and a fault decision module. The frequency estimator is implemented by a zoom technique and a high-resolution analysis technique known as the estimation of signal parameters via rotational invariance techniques, which can extract frequencies accurately. For the amplitude estimator, a least squares estimator is derived to obtain amplitudes of fault harmonics, without frequency leakage.
In the fault decision module, the fault diagnosis index from the amplitude estimator is used depending on the load conditions of the induction motors. The fault index and corresponding threshold are optimized by using the false alarm and detection probabilities.
Experimental results obtained from induction motors show that the proposed diagnosis algorithm is capable of detecting BRB faults with an accuracy that is superior to the zoom-based MUSIC algorithm.
The proposed method employs a frequency estimator, an amplitude estimator, and a fault decision module. The frequency estimator is implemented by a zoom technique and a high-resolution analysis technique known as the estimation of signal parameters via rotational invariance techniques, which can extract frequencies accurately. For the amplitude estimator, a least squares estimator is derived to obtain amplitudes of fault harmonics, without frequency leakage.
In the fault decision module, the fault diagnosis index from the amplitude estimator is used depending on the load conditions of the induction motors. The fault index and corresponding threshold are optimized by using the false alarm and detection probabilities.
Experimental results obtained from induction motors show that the proposed diagnosis algorithm is capable of detecting BRB faults with an accuracy that is superior to the zoom-based MUSIC algorithm.
High-Speed Hardware Arbitration Supporting Priorities and Bounded Service Latency
Effective utilization of the available resources in network processors and in modern embedded multicore systems primarily requires advanced hardware-based scheduling techniques to manage increasing arbitration rates. In this scope, this letter presents the architecture and a low-cost ultra high-speed implementation of a novel arbiter.
While average response time or service throughput is often an inadequate metric when dealing with strict time constraints, the proposed hardware scheme features an innovative scheduling technique supporting prioritization, while at the same time this arbiter guarantees bounded service latency. Based on a dual priority enforcer scheme, a 64-input scheduler is implemented in a standard 0.13 um CMOS technology making approximately over 200 million scheduling decisions per second.
While average response time or service throughput is often an inadequate metric when dealing with strict time constraints, the proposed hardware scheme features an innovative scheduling technique supporting prioritization, while at the same time this arbiter guarantees bounded service latency. Based on a dual priority enforcer scheme, a 64-input scheduler is implemented in a standard 0.13 um CMOS technology making approximately over 200 million scheduling decisions per second.
High-Temperature UHF RFID Sensor Measurements in a Full-Metal Environment
Nowadays UHF RFID systems are used in several sensor applications. We present an RFID system that is used in switchgears to monitor the temperature of the contact points of copper busbars. The switchgear is equipped with an RFID reader and several RFID tags. Each tag is build up by an RFID chip, an internal microcontroller and a temperature sensor.
This system is designed to withstand and measure temperatures up to 170 C. The paper presents the design of the RFID sensor tag and some insights of the HF path in a full metal enclosure.
This system is designed to withstand and measure temperatures up to 170 C. The paper presents the design of the RFID sensor tag and some insights of the HF path in a full metal enclosure.
HMM-based Human Fall Detection and Prediction Method using Tri-Axial Accelerometer
Falls in the elderly have always been a serious medical and social problem. To detect and predict falls, a hidden Markov model (HMM)-based method using tri-axial accelerations of human body is proposed. A wearable motion detection device using tri-axial accelerometer is designed and realized, which can detect and predict falls based on tri-axial acceleration of human upper trunk.
The acceleration time series (ATS) extracted from human motion processes are used to describe human motion features, and the ATS extracted from human fall courses but before the collision are used to train HMM so as to build a random process mathematical model.
Thus, the outputs of HMM, which express the marching degrees of input ATS and HMM, can be used to evaluate the risks to fall. The experiment results show that fall events can be predicted 200-400 ms ahead the occurrence of collisions, and distinguished from other daily life activities with an accuracy of 100%.
The acceleration time series (ATS) extracted from human motion processes are used to describe human motion features, and the ATS extracted from human fall courses but before the collision are used to train HMM so as to build a random process mathematical model.
Thus, the outputs of HMM, which express the marching degrees of input ATS and HMM, can be used to evaluate the risks to fall. The experiment results show that fall events can be predicted 200-400 ms ahead the occurrence of collisions, and distinguished from other daily life activities with an accuracy of 100%.
Human Health Monitoring Mobile Phone Application by using the Wireless sensor based Embedded System
Nowadays population growth increased exponentially and health diseases also increase parallel because the persons do not give important about the body conditions due to time allocation and highly expensive medical treatment. In this paper deals with this problem by using the nano sensor based mobile phones.
Nano sensor was placed in the mobile phones. It's used to monitor the human body because now most of the peoples having the mobilesphones. This mobile phone having the in build highly sensitive TI MSP430 family microcontroller and zigbee used to transmit the health care data's. Compare to the other microcontroller, TI MSP430 was secured for the patient health. The nanosensor used to detect the minute variations in the human body without need various types of sensor.
In this device used to monitor and measure the ASTHMA, CANCER, and BLOODPRESURE, ECG from the human breathing and body temperature. In this device alert the patient and display what is the body condition, causes, how to overcome this problems without need proper physician guides' and save the money.
Five are more patient combined to make one wireless network with any one of the hospital management. The hospital management continuously monitor the patient health condition if any variations occurs in below or above to the normal range immediately making call to the patient home and also call the ambulance. The location of the person detected by using the GPRS tracking system.
Nano sensor was placed in the mobile phones. It's used to monitor the human body because now most of the peoples having the mobilesphones. This mobile phone having the in build highly sensitive TI MSP430 family microcontroller and zigbee used to transmit the health care data's. Compare to the other microcontroller, TI MSP430 was secured for the patient health. The nanosensor used to detect the minute variations in the human body without need various types of sensor.
In this device used to monitor and measure the ASTHMA, CANCER, and BLOODPRESURE, ECG from the human breathing and body temperature. In this device alert the patient and display what is the body condition, causes, how to overcome this problems without need proper physician guides' and save the money.
Five are more patient combined to make one wireless network with any one of the hospital management. The hospital management continuously monitor the patient health condition if any variations occurs in below or above to the normal range immediately making call to the patient home and also call the ambulance. The location of the person detected by using the GPRS tracking system.
Human Operator Studies of Portable Touch screen Crane Control Interfaces
Controlling a crane is often very difficult for human operators due to the slow response of the heavy structures and the lightly-damped payload oscillation. Manipulation tasks are made even harder when the interface between the human and crane is unintuitive.
Although there have recently been significant advancements in portable electronic devices, this useful technology has not migrated into crane control applications. In order to facilitate this technology cross over, this paper presents results from an operator study that evaluated various user interfaces for a touchscreen crane controller.
Although there have recently been significant advancements in portable electronic devices, this useful technology has not migrated into crane control applications. In order to facilitate this technology cross over, this paper presents results from an operator study that evaluated various user interfaces for a touchscreen crane controller.
Hybrid Analysis in the Latent Nestling Method Applied to Fault Diagnosis
This paper presents the Latent Nestling Method (LNM) formalization in hybrid systems. For the proposed LNM, it is necessary to include places of continuous or differential character, allowing the analysis of continuous dynamical variable. This paper is a continuation of our previous papers , . Here, the LNM is exploited to analyze the extension to hybrid systems.
One of the contributions of this work is a practical application of the LNM in hybrid systems. The case study is the Lubrication and Cooling system of a Wind Turbine Gearbox. The model of the system is built using colored Petri nets formalism and the classic techniques of continuous and hybrid Petri nets. Simulation results are presented to validate some key concepts of the formalization in hybrid systems.
One of the contributions of this work is a practical application of the LNM in hybrid systems. The case study is the Lubrication and Cooling system of a Wind Turbine Gearbox. The model of the system is built using colored Petri nets formalism and the classic techniques of continuous and hybrid Petri nets. Simulation results are presented to validate some key concepts of the formalization in hybrid systems.
Hybrid RFID System-based Pedestrian Localization: A Case Study
Localization systems using RFID - especially passive RFID - are coming increasingly under the spotlight. Passive RFID has a relatively small sensing range compared to other radio-frequency-based localization techniques. Therefore in practice the deployed tags may not cover the whole scene of interest.
Additionally, in the area of pedestrian localization, the unpredictable movement of pedestrians makes a complete RFID tag coverage extremely difficult. This paper introduces a hybrid RFID localization system used for indoor pedestrians to overcome the coverage shortfall associated with passive RFID tags. Two extra sources are used to assist the RFID system: local INS sensors and ZigBee nodes. A particle filter serves as a fusion framework.
A test scenario was built with 220 RFID tags and 8 ZigBee nodes deployed in a museum. Different algorithms were evaluated in this deployment. The results show that the hybrid approach produces robust localization even with a low number of tags.
Additionally, in the area of pedestrian localization, the unpredictable movement of pedestrians makes a complete RFID tag coverage extremely difficult. This paper introduces a hybrid RFID localization system used for indoor pedestrians to overcome the coverage shortfall associated with passive RFID tags. Two extra sources are used to assist the RFID system: local INS sensors and ZigBee nodes. A particle filter serves as a fusion framework.
A test scenario was built with 220 RFID tags and 8 ZigBee nodes deployed in a museum. Different algorithms were evaluated in this deployment. The results show that the hybrid approach produces robust localization even with a low number of tags.
Implementation of a CAN-based multi controller digital driving system for a vehicle
A high performance bidirectional DC/AC converter is required for low emission and high efficiency propulsion systems, such as electric vehicles (EVs) and hybrid electric vehicles (HEVs). In order to increase the reliability of the drive system, this paper presents the design, analysis, and implementation of a cost effective sensorless control scheme for the extensively used brushless DC motors and alternators.
Taking into consideration cost and ease of implementation, the commutation signals are obtained without the motor neutral voltage, multistage analog filters, A/D converters, and the complex digital phase shift (delay) circuit which are indispensable in the conventional sensorless control algorithms. In the proposed approach, instead of detecting the zero crossing point of the non-excited phase back EMF to the neutral voltage, the commutation signals are extracted directly from the specific average line to line voltages with simple RC circuits and comparators.
As a result, the proposed control algorithm can be easily implemented with the low cost CPLDs or 8-bit micro-controllers. Because of the inherent low cost property, the proposed control algorithm is particularly suitable for cost sensitive products such as electric bikes, electric scooters, hybrid electric scooters, home appliances, automotive components, etc. Theoretical analysis and experimental results show that the proposed control algorithm exhibits satisfactory performance over a wide operation range in both motor and alternator operations
Taking into consideration cost and ease of implementation, the commutation signals are obtained without the motor neutral voltage, multistage analog filters, A/D converters, and the complex digital phase shift (delay) circuit which are indispensable in the conventional sensorless control algorithms. In the proposed approach, instead of detecting the zero crossing point of the non-excited phase back EMF to the neutral voltage, the commutation signals are extracted directly from the specific average line to line voltages with simple RC circuits and comparators.
As a result, the proposed control algorithm can be easily implemented with the low cost CPLDs or 8-bit micro-controllers. Because of the inherent low cost property, the proposed control algorithm is particularly suitable for cost sensitive products such as electric bikes, electric scooters, hybrid electric scooters, home appliances, automotive components, etc. Theoretical analysis and experimental results show that the proposed control algorithm exhibits satisfactory performance over a wide operation range in both motor and alternator operations
Indoor Positioning: A Review of Indoor Ultrasonic Positioning systems
In order to provide location information for indoor applications and context-aware computing, a lot of research is being done since last decade for development of real-time Indoor location system. In this paper, we have investigated indoor location concepts and have focused two major technologies used in many indoor location systems i.e. RF and ultrasonic.
An overview of various RF systems that use different RF properties for location estimation has been given. Ultrasonic systems have been reviewed in detail as they provide low cost fine grained location systems.
A few well known ultrasonic location systems have been investigated with a comparison of the system based on performance, accuracy and limitations.
An overview of various RF systems that use different RF properties for location estimation has been given. Ultrasonic systems have been reviewed in detail as they provide low cost fine grained location systems.
A few well known ultrasonic location systems have been investigated with a comparison of the system based on performance, accuracy and limitations.
Induction Machine Fault Diagnosis using Microcontroller and Real Time Digital Simulation Unit Ethernet enabled Digital I/O Control in Embedded System
In an approach to diagnose the various types of fault, generally occurred in Induction machines, this paper describes a monitoring and analysis system. The induction machine model and its various types of fault are simulated using a Real Time Digital Simulation (RTDS) unit.
The signal corresponding to the simulation can be taken out of the RTDS unit which is interfaced with a microcontroller for its acquisition in a PC. The PC based software can store it and the fault detection algorithm (sequence component based) runs over it to detect and diagnose the fault. Encouraging results are obtained.
The signal corresponding to the simulation can be taken out of the RTDS unit which is interfaced with a microcontroller for its acquisition in a PC. The PC based software can store it and the fault detection algorithm (sequence component based) runs over it to detect and diagnose the fault. Encouraging results are obtained.
Integration and Operation of a Single-Phase Bidirectional Inverter with Two Buck/Boost MPPTS for DC-Distribution Applications
This study is focused on integration and operation of a single-phase bidirectional inverter with two buck/boost maximum power point trackers (MPPTs) for dc-distribution applications. In a dc-distribution system, a bidirectional inverter is required to control the power flow between dc bus and ac grid, and to regulate the dc bus to a certain range of voltages.
A droop regulation mechanism according to the inverter inductor current levels to reduce capacitor size, balance power flow, and accommodate load variation is proposed. Since the photovoltaic (PV) array voltage can vary from 0 to 600 V, especially with thin-film PV panels, the MPPT topology is formed with buck and boost converters to operate at the dc-bus voltage around 380 V, reducing the voltage stress of its followed inverter.
Additionally, the controller can online check the input configuration of the two MPPTs, equally distribute the PV-array output current to the two MPPTs in parallel operation, and switch control laws to smooth out mode transition. A comparison between the conventional boost MPPT and the proposed buck/boost MPPT integrated with a PV inverter is also presented. Experimental results obtained from a 5-kW system have verified the discussion and feasibility.
A droop regulation mechanism according to the inverter inductor current levels to reduce capacitor size, balance power flow, and accommodate load variation is proposed. Since the photovoltaic (PV) array voltage can vary from 0 to 600 V, especially with thin-film PV panels, the MPPT topology is formed with buck and boost converters to operate at the dc-bus voltage around 380 V, reducing the voltage stress of its followed inverter.
Additionally, the controller can online check the input configuration of the two MPPTs, equally distribute the PV-array output current to the two MPPTs in parallel operation, and switch control laws to smooth out mode transition. A comparison between the conventional boost MPPT and the proposed buck/boost MPPT integrated with a PV inverter is also presented. Experimental results obtained from a 5-kW system have verified the discussion and feasibility.
Intelligent Monitoring and Control Rendered to Street Lighting
Intelligent Monitoring and Control Rendered to Street Lighting is a novel idea to wirelessly control street lights. Every individual streetlight i.e. node has a unique IPv6 and IEEE address through which it can be controlled from the control centre. The system is designed using a microcontroller MSP430F6636 and an RF IC CC1180. The RF IC is used for sending and receiving the monitoring and control signals to and from the control centre.
The microcontroller processes the signals obtained from the RF IC as well as the lamp. Messages are sent from control centre to nodes via gateway, which is a node with a GPRS module. The gateway passes the messages to the respective nodes by hopping the message between the nodes. The communication between nodes takes place in ISM band and that between gateway and control centre through GPRS.
Automatic as well as manual remote switching on or off of individual lamps, controlling their light intensity and acquisition of status and failure is possible. Through this system we can save almost 50% of the power consumed just by strategically dimming lights. Maintenance and patrol costs are also reduced. This paper attempts to make this system as flexible, compact and cost effective as possible, also the front end can be modified to suit any application.
The microcontroller processes the signals obtained from the RF IC as well as the lamp. Messages are sent from control centre to nodes via gateway, which is a node with a GPRS module. The gateway passes the messages to the respective nodes by hopping the message between the nodes. The communication between nodes takes place in ISM band and that between gateway and control centre through GPRS.
Automatic as well as manual remote switching on or off of individual lamps, controlling their light intensity and acquisition of status and failure is possible. Through this system we can save almost 50% of the power consumed just by strategically dimming lights. Maintenance and patrol costs are also reduced. This paper attempts to make this system as flexible, compact and cost effective as possible, also the front end can be modified to suit any application.
Intelligent Parking System for Car Parking Guidance and Damage Notification
This paper presents an innovative intelligent parking system (IPS) that has two functions: Car parking guidance and car damage notification. IPS is an advanced automatic driving system that consists of car guidance which proposes oriented assistance for drivers while parking.
IPS has some interesting functionalities that ensure an easy parking without damages, parking within less time in any suitable spots and getting a notification if the parked car has been scratched or damaged while the driver is not in the car. The main purpose of the IPS system considers a control car system, an algorithmic move car system and a damage notification system to the vehicle.
During the parking process, the driver is alerted by visual and sound signals. The IPS system provides a path planning image that is displayed on the on-board computer system to indicate the directions for the wheels. The damage notification system consists of car-camera shock sensors placed in the front and rear of the vehicle that record the incident when the driver is not in the car.
IPS has some interesting functionalities that ensure an easy parking without damages, parking within less time in any suitable spots and getting a notification if the parked car has been scratched or damaged while the driver is not in the car. The main purpose of the IPS system considers a control car system, an algorithmic move car system and a damage notification system to the vehicle.
During the parking process, the driver is alerted by visual and sound signals. The IPS system provides a path planning image that is displayed on the on-board computer system to indicate the directions for the wheels. The damage notification system consists of car-camera shock sensors placed in the front and rear of the vehicle that record the incident when the driver is not in the car.
Intelligent Technologies for Self-Sustaining, RFID-Based, Rural E-Health Systems
The paper states that community-based healthcare is increasingly important for the well-being of inhabitants of emerging economies. The community model is needed partly because roads are less developed, limiting patients ability to commute from distant villages to central medical facilities. Also, developing countries have a large rural population base. Some estimates are that rural agriculture employs 75% of the population in developing countries.
The goal of an RFID-backed community healthcare solution is to enable easy and reliable identification of individual patients, maintain more accurate medical records, facilitate better healthcare, and enhance the quality of life in communities that are remote from a central medical facility.
In addition, it can also help to relieve the workload pressure on the central medical facility when it is overcrowded and can increase revenue opportunities by broadening the base of patients to include more remote locations. It may also help to improve the efficiency of the central medical facility, allowing it to focus resources on cases that require more specialized attention and care.
The goal of an RFID-backed community healthcare solution is to enable easy and reliable identification of individual patients, maintain more accurate medical records, facilitate better healthcare, and enhance the quality of life in communities that are remote from a central medical facility.
In addition, it can also help to relieve the workload pressure on the central medical facility when it is overcrowded and can increase revenue opportunities by broadening the base of patients to include more remote locations. It may also help to improve the efficiency of the central medical facility, allowing it to focus resources on cases that require more specialized attention and care.
Intelligent Vehicle Monitoring System using Wireless Communication on PSoC
The use of mobile phones while driving is one of the most dangerous and widely seen causes of fatal road accidents. The objective of the paper is to develop a device to find people who use mobile phones while driving and evade from stringent laws enforced by the government easily.
This novel and ingenious technique facilitates the government to take adequate action against those who are violating these laws. To meet the requirements of an intelligent vehicle monitoring system, this architecture integrates Global Position System (GPS), Global System for Mobile communications (GSM) and a Microcontroller in the whole.
This device is used to prevent texting and calling of mobile phones while driving vehicles. If the driver is using the phone while the vehicle is in motion, it triggers a signal which notifies the cops with the vehicle's number plate and the location with the help of GPS system. It receives the mobile signal and detects the presence of mobile. This signal eventually triggers the microcontroller with a glowing LED. Due to the voltage fluctuation, the message is sent to the cops using GSM communication.
This novel and ingenious technique facilitates the government to take adequate action against those who are violating these laws. To meet the requirements of an intelligent vehicle monitoring system, this architecture integrates Global Position System (GPS), Global System for Mobile communications (GSM) and a Microcontroller in the whole.
This device is used to prevent texting and calling of mobile phones while driving vehicles. If the driver is using the phone while the vehicle is in motion, it triggers a signal which notifies the cops with the vehicle's number plate and the location with the help of GPS system. It receives the mobile signal and detects the presence of mobile. This signal eventually triggers the microcontroller with a glowing LED. Due to the voltage fluctuation, the message is sent to the cops using GSM communication.
Localization of Wireless Sensor Networks in the Wild: Pursuit of Ranging Quality
Localization is a fundamental issue of wireless sensor networks that has been extensively studied in the literature. Our real-world experience from GreenOrbs, a sensor network system deployed in a forest, shows that localization in the wild remains very challenging due to various interfering factors.
In this paper, we propose CDL, a Combined and Differentiated Localization approach for localization that exploits the strength of range-free approaches and range-based approaches using received signal strength indicator (RSSI). A critical observation is that ranging quality greatly impacts the overall localization accuracy. To achieve a better ranging quality, our method CDL incorporates virtual-hop localization, local filtration, and ranging-quality aware calibration.
We have implemented and evaluated CDL by extensive real-world experiments in GreenOrbs and large-scale simulations. Our experimental and simulation results demonstrate that CDL outperforms current state-of-art localization approaches with a more accurate and consistent performance. For example, the average location error using CDL in GreenOrbs system is 2.9 m, while the previous best method SISR has an average error of 4.6 m.
In this paper, we propose CDL, a Combined and Differentiated Localization approach for localization that exploits the strength of range-free approaches and range-based approaches using received signal strength indicator (RSSI). A critical observation is that ranging quality greatly impacts the overall localization accuracy. To achieve a better ranging quality, our method CDL incorporates virtual-hop localization, local filtration, and ranging-quality aware calibration.
We have implemented and evaluated CDL by extensive real-world experiments in GreenOrbs and large-scale simulations. Our experimental and simulation results demonstrate that CDL outperforms current state-of-art localization approaches with a more accurate and consistent performance. For example, the average location error using CDL in GreenOrbs system is 2.9 m, while the previous best method SISR has an average error of 4.6 m.
Location-Aware and Safer Cards: Enhancing RFID Security and Privacy via Location Sensing
In this paper, we report on a new approach for enhancing security and privacy in certain RFID applications whereby location or location-related information (such as speed) can serve as a legitimate access context. Examples of these applications include access cards, toll cards, credit cards, and other payment tokens.
We show that location awareness can be used by both tags and back-end servers for defending against unauthorized reading and relay attacks on RFID systems. On the tag side, we design a location-aware selective unlocking mechanism using which tags can selectively respond to reader interrogations rather than doing so promiscuously.
On the server side, we design a location-aware secure transaction verification scheme that allows a bank server to decide whether to approve or deny a payment transaction and detect a specific type of relay attack involving malicious readers. The premise of our work is a current technological advancement that can enable RFID tags with low-cost location (GPS) sensing capabilities. Unlike prior research on this subject, our defenses do not rely on auxiliary devices or require any explicit user involvement.
We show that location awareness can be used by both tags and back-end servers for defending against unauthorized reading and relay attacks on RFID systems. On the tag side, we design a location-aware selective unlocking mechanism using which tags can selectively respond to reader interrogations rather than doing so promiscuously.
On the server side, we design a location-aware secure transaction verification scheme that allows a bank server to decide whether to approve or deny a payment transaction and detect a specific type of relay attack involving malicious readers. The premise of our work is a current technological advancement that can enable RFID tags with low-cost location (GPS) sensing capabilities. Unlike prior research on this subject, our defenses do not rely on auxiliary devices or require any explicit user involvement.
Locking and Unlocking of Theft Vehicles Using CAN
Avoiding Vehicle Theft is making buzz in present automobile industry. Design and development of a theft control system for an automobile, can be achieved by making use of GPS feature of mobile phone. The developed system makes use of an mobile phone that is embedded in the vehicle with an interfacing to Engine Control Module(ECM) through Control Area Network (CAN) Bus, which is in turn, communicated to the ECM.
The vehicle being stolen can be stopped by using GPS feature of mobile phone and this information is used by the owner of the vehicle for future processing. The owner sends the message to the mobile which is embedded in the vehicle which has stolen which in turn controls the vehicles engine by locking the working of the engine immediately.
The developed system accept the message and broadcasted to the Vehicle Network through CAN Bus. The engine can be unlocked only by the owner of the vehicle by sending the message again. The goal behind the design is to develop security for vehicles and embedded system to communicate with engine of the vehicle.
The vehicle being stolen can be stopped by using GPS feature of mobile phone and this information is used by the owner of the vehicle for future processing. The owner sends the message to the mobile which is embedded in the vehicle which has stolen which in turn controls the vehicles engine by locking the working of the engine immediately.
The developed system accept the message and broadcasted to the Vehicle Network through CAN Bus. The engine can be unlocked only by the owner of the vehicle by sending the message again. The goal behind the design is to develop security for vehicles and embedded system to communicate with engine of the vehicle.
Micro-power Design of a Fully Autonomous Energy Harvesting Circuit for Arrays of Piezoelectric Transducers
This paper presents a self-powered energy harvesting circuit based on synchronous charge extraction with a single shared inductor for power conversion from arrays of independent piezoelectric transducers. The number of handled elements can be easily increased at the expense of few additional components and without affecting performance. The energy harvesting circuit was characterized with three 0.5×12.7×31.8 mm3 piezoelectric cantilevers subject to different types of vibrations.
Throughout all operating conditions, the circuit was able to extract the maximum power independently from every transducer. Compared to passive energy harvesting interfaces, the output power is significantly higher, with worst-case increases ranging from +75% to +184%.
The circuit starts up passively and is based on ultra-low power active control, which consumes during operation at 3 V a fraction of the extra harvested power as low as 10 ??W per source. As part of the best trade-off between harvested and intrinsic power, an overall energy efficiency up to 74% was achieved.
Throughout all operating conditions, the circuit was able to extract the maximum power independently from every transducer. Compared to passive energy harvesting interfaces, the output power is significantly higher, with worst-case increases ranging from +75% to +184%.
The circuit starts up passively and is based on ultra-low power active control, which consumes during operation at 3 V a fraction of the extra harvested power as low as 10 ??W per source. As part of the best trade-off between harvested and intrinsic power, an overall energy efficiency up to 74% was achieved.
Minimal Grasper: A Practical Robotic Grasper With Robust Performance for Pick-and-Place Tasks
In this paper, a flexible enveloping grasper is proposed for pick-and-place tasks with low manipulation and task planning complexity for practical applications. The proposed grasper has two main characteristics: self-adaptivity and flexibility.
Self-adaptivity means that the proposed grasper can grip an object in a self-adaptive way such that various process complexities (e.g., sensing, force control, and sensor-motor coordination) are significantly reduced. By flexibility, we mean that, by using a flexible material, a stable grip can be implemented to cause increased friction between the grasper and the target object as a result of increased contact area.
These two properties help the proposed grasper to minimize internal forces in a passive manner and to achieve successful force distribution with self-adaptivity when performing enveloping grasping. Three sets of experiments were performed with an average success rate of 93.2% in pick-and-place tasks
Self-adaptivity means that the proposed grasper can grip an object in a self-adaptive way such that various process complexities (e.g., sensing, force control, and sensor-motor coordination) are significantly reduced. By flexibility, we mean that, by using a flexible material, a stable grip can be implemented to cause increased friction between the grasper and the target object as a result of increased contact area.
These two properties help the proposed grasper to minimize internal forces in a passive manner and to achieve successful force distribution with self-adaptivity when performing enveloping grasping. Three sets of experiments were performed with an average success rate of 93.2% in pick-and-place tasks
Mobile Phones as Seismologic Sensors Automating Data Extraction for the iShake System
There are a variety of approaches to seismic sensing, which range from collecting sparse measurements with high-fidelity seismic stations to non-quantitative, post-earthquake surveys. The sparse nature of the high-fidelity stations and the inaccuracy of the surveys create the need for a high-density, semi-quantitative approach to seismic sensing.
To fill this void, the UC Berkeley iShake project designed a mobile client-backend server architecture that uses sensor-equipped mobile devices to measure earthquake ground shaking. iShake provides the general public with a service to more easily contribute more quantitatively significant data to earthquake research by automating the data collection and reporting mechanisms via the iShake mobile application.
The devices act as distributed sensors that enable measurements to be taken and transmitted with a cellular network connection. Shaking table testing was used to assess the quality of the measurements obtained from the iPhones and iPods on a benchmark of 150 ground motions. Once triggered by a shaking event, the devices transmit sensor data to a backend server for further processing. After a seismic event is verified by high-fidelity stations, filtering algorithms are used to detect falling phones, as well as device-specific responses to the event.
A method was developed to determine the absolute orientation of a device to estimate the direction of first motion of a seismic event. A “virtual earthquake” pilot test was conducted on the UC Berkeley campus to verify the operation of the iShake system.
By designing and fully implementing a system architecture, developing signal processing techniques unique to mobile sensing, and conducting shaking table tests to confirm the validity of the sensing platform, the iShake project serves as foundational work for further studies in seismic sensing on mobile devices.
To fill this void, the UC Berkeley iShake project designed a mobile client-backend server architecture that uses sensor-equipped mobile devices to measure earthquake ground shaking. iShake provides the general public with a service to more easily contribute more quantitatively significant data to earthquake research by automating the data collection and reporting mechanisms via the iShake mobile application.
The devices act as distributed sensors that enable measurements to be taken and transmitted with a cellular network connection. Shaking table testing was used to assess the quality of the measurements obtained from the iPhones and iPods on a benchmark of 150 ground motions. Once triggered by a shaking event, the devices transmit sensor data to a backend server for further processing. After a seismic event is verified by high-fidelity stations, filtering algorithms are used to detect falling phones, as well as device-specific responses to the event.
A method was developed to determine the absolute orientation of a device to estimate the direction of first motion of a seismic event. A “virtual earthquake” pilot test was conducted on the UC Berkeley campus to verify the operation of the iShake system.
By designing and fully implementing a system architecture, developing signal processing techniques unique to mobile sensing, and conducting shaking table tests to confirm the validity of the sensing platform, the iShake project serves as foundational work for further studies in seismic sensing on mobile devices.
Model Predictive and Genetic Algorithm-Based Optimization of Residential Temperature Control in the Presence of Time-Varying Electricity Prices
This paper presents an optimal control algorithm for residential temperature regulation. The combination of concepts from system identification, model-predictive control, and genetic algorithms result in an optimization methodology capable of achieving an acceptable compromise between comfort and cost in the presence of constant as well as time-varying electricity prices.
Simulation results demonstrate that the proposed approach has the potential to achieve substantial energy savings and cost reductions while maintaining acceptable comfort levels with minimal consumer participation.
Simulation results demonstrate that the proposed approach has the potential to achieve substantial energy savings and cost reductions while maintaining acceptable comfort levels with minimal consumer participation.
Modeling of Driver Behavior in Real World Scenarios using Multiple Noninvasive Sensors
With the development of new in-vehicle technology, drivers are exposed to more sources of distraction, which can lead to an unintentional accident. Monitoring the driver attention level has become a relevant research problem. This is the precise aim of this study. A database containing 20 drivers was collected in real-driving scenarios. The drivers were asked to perform common secondary tasks such as operating the radio, phone and a navigation system.
The collected database comprises of various noninvasive sensors including the controller area network-bus (CAN-Bus), video cameras and microphone arrays. The study analyzes the effects in driver behaviors induced by secondary tasks. The corpus is analyzed to identify multimodal features that can be used to discriminate between normal and task driving conditions.
Separate binary classifiers are trained to distinguish between normal and each of the secondary tasks, achieving an average accuracy of 77.2%. When a joint, multi-class classifier is trained, the system achieved accuracies of 40.8%, which is significantly higher than chances (12.5%).
We observed that the classifiers' accuracy varies across secondary tasks, suggesting that certain tasks are more distracting than others. Motivated by these results, the study builds statistical models in the form of Gaussian Mixture Models (GMMs) to quantify the actual deviations in driver behaviors from the expected normal driving patterns.
The study includes task independent and task dependent models. Building upon these results, a regression model is proposed to obtain a metric that characterizes the attention level of the driver. This metric can be used to signal alarms, preventing collision and improving the overall driving experience.
The collected database comprises of various noninvasive sensors including the controller area network-bus (CAN-Bus), video cameras and microphone arrays. The study analyzes the effects in driver behaviors induced by secondary tasks. The corpus is analyzed to identify multimodal features that can be used to discriminate between normal and task driving conditions.
Separate binary classifiers are trained to distinguish between normal and each of the secondary tasks, achieving an average accuracy of 77.2%. When a joint, multi-class classifier is trained, the system achieved accuracies of 40.8%, which is significantly higher than chances (12.5%).
We observed that the classifiers' accuracy varies across secondary tasks, suggesting that certain tasks are more distracting than others. Motivated by these results, the study builds statistical models in the form of Gaussian Mixture Models (GMMs) to quantify the actual deviations in driver behaviors from the expected normal driving patterns.
The study includes task independent and task dependent models. Building upon these results, a regression model is proposed to obtain a metric that characterizes the attention level of the driver. This metric can be used to signal alarms, preventing collision and improving the overall driving experience.
Monitoring the Marine Atmospheric Refractivity Profiles by Ground-based GPS Occultation
GPS radio occultation has proved to be a powerful tool for remotely sensing the Earth's neutral atmosphere and ionosphere. In this letter, we propose a novel approach to retrieving marine tropospheric profiles based on single ground-based GPS occultation observations.
A new retrieval method uses the data from a ground-based receiver while the GPS satellites rise or set at the local horizon in the direction of the ocean. The GPS L1 amplitude signals with negative elevation angles are used to retrieve the atmospheric refractivity by artificial neutral networks. The subsequent experiment was carried out on the coast of the Yellow Sea from August 2010 to July 2011. It is shown that the inversion profiles are very consistent with the radiosonde observations.
The new method outperforms the Hopfield model, particularly at 0.5-5-km altitude. These results validate the feasibility of retrieving the lower marine atmospheric refractivity from GPS data collected by a single ground-based receiver near the sea surface.
A new retrieval method uses the data from a ground-based receiver while the GPS satellites rise or set at the local horizon in the direction of the ocean. The GPS L1 amplitude signals with negative elevation angles are used to retrieve the atmospheric refractivity by artificial neutral networks. The subsequent experiment was carried out on the coast of the Yellow Sea from August 2010 to July 2011. It is shown that the inversion profiles are very consistent with the radiosonde observations.
The new method outperforms the Hopfield model, particularly at 0.5-5-km altitude. These results validate the feasibility of retrieving the lower marine atmospheric refractivity from GPS data collected by a single ground-based receiver near the sea surface.
Motion Planning and Stabilization Control of a Multipropeller Multifunction Aerial Robot
A multipropeller multifunction aerial robot capable of flight and wall climbing is presented in this paper. This novel robot consists of four propellers and two leg-wheel mechanisms. The propellers providing thrust for the vehicle are devoted to the attitude control. Two leg-wheel mechanisms are used for the wall climbing.
The dynamic modeling in flight mode is derived in terms of the coupling between the main body and the legs. The wall-climbing mode of the robot falls into wheel-wall-climbing mode and leg-wall-climbing mode, while the latter is the focus of this paper.
The kinematic and dynamic modeling, as well as the constraints in leg-wall-climbing mode are investigated. Based on the model, the leg-wall-climbing motion planning is proposed in terms of the constraints. The paper also presents a stabilization control strategy to maintain the attitude stability when the aerial robot is in leg-wall-climbing mode.
Simulations of the robot in leg-wall-climbing mode are accomplished to show the effectiveness of the designed stabilization controller at the presence of input disturbances, sensor noise, sensor delays, and parametric modeling errors. A quadrotor subsystem experimental platform is built, and the experimental results support the theoretical analysis.
The dynamic modeling in flight mode is derived in terms of the coupling between the main body and the legs. The wall-climbing mode of the robot falls into wheel-wall-climbing mode and leg-wall-climbing mode, while the latter is the focus of this paper.
The kinematic and dynamic modeling, as well as the constraints in leg-wall-climbing mode are investigated. Based on the model, the leg-wall-climbing motion planning is proposed in terms of the constraints. The paper also presents a stabilization control strategy to maintain the attitude stability when the aerial robot is in leg-wall-climbing mode.
Simulations of the robot in leg-wall-climbing mode are accomplished to show the effectiveness of the designed stabilization controller at the presence of input disturbances, sensor noise, sensor delays, and parametric modeling errors. A quadrotor subsystem experimental platform is built, and the experimental results support the theoretical analysis.
Moving Cells: A Promising Solution to Boost Performance for Vehicular Users
In future wireless networks, a significant number of users accessing wireless broadband will be vehicular (i.e., in public transportation vehicles like buses, trams, or trains). The Third Generation Partnership Project has started to investigate how to serve these vehicular users cost-effectively, and several solutions have been proposed.
One promising solution is to deploy a moving relay node (MRN), on a public transportation vehicle that forms its own cell inside the vehicle to serve vehicular users. By proper antenna placement, an MRN can reduce or even eliminate the vehicular penetration loss that affects communication.
Moreover, MRNs can exploit various smart antenna techniques and advanced signal processing schemes, as they are less limited by size and power than regular user equipment. However, there are also challenges in using MRNs, such as designing efficient interference management techniques as well as proper mobility management schemes to exploit the benefit of group handovers for vehicular UE devices served by the same MRN.
Nevertheless, initial system-level evaluation results indicate that a dedicated MRN deployment shows great potential to improve the vehicular user experience, and thereby can potentially bring significant benefits to future wireless communication systems.
One promising solution is to deploy a moving relay node (MRN), on a public transportation vehicle that forms its own cell inside the vehicle to serve vehicular users. By proper antenna placement, an MRN can reduce or even eliminate the vehicular penetration loss that affects communication.
Moreover, MRNs can exploit various smart antenna techniques and advanced signal processing schemes, as they are less limited by size and power than regular user equipment. However, there are also challenges in using MRNs, such as designing efficient interference management techniques as well as proper mobility management schemes to exploit the benefit of group handovers for vehicular UE devices served by the same MRN.
Nevertheless, initial system-level evaluation results indicate that a dedicated MRN deployment shows great potential to improve the vehicular user experience, and thereby can potentially bring significant benefits to future wireless communication systems.
MSU Jumper: A Single-Motor-Actuated Miniature Steerable Jumping Robot
The ability to jump is found widely among small animals such as frogs, grasshoppers, and fleas. They jump to overcome large obstacles relative to their small sizes. Inspired by the animals' jumping capability, a miniature jumping robot-Michigan State University (MSU) Jumper-has been developed. In this paper, the mechanical design, fabrication, and experimentation of the MSU jumper are presented.
The robot can achieve the following three performances simultaneously, which distinguish it from the other existing jumping robots. First, it can perform continuous steerable jumping that is based on the self-righting and the steering capabilities. Second, the robot only requires a single actuator to perform all the functions.
Third, the robot has a light weight (23.5 g) to reduce the damage that results from the impact of landing. Experimental results show that, with a 75° take-off angle, the robot can jump up to 87 cm in vertical height and 90 cm in horizontal distance.
The robot has a wide range of applications such as sensor/communication networks, search and rescue, surveillance, and environmental monitoring.
The robot can achieve the following three performances simultaneously, which distinguish it from the other existing jumping robots. First, it can perform continuous steerable jumping that is based on the self-righting and the steering capabilities. Second, the robot only requires a single actuator to perform all the functions.
Third, the robot has a light weight (23.5 g) to reduce the damage that results from the impact of landing. Experimental results show that, with a 75° take-off angle, the robot can jump up to 87 cm in vertical height and 90 cm in horizontal distance.
The robot has a wide range of applications such as sensor/communication networks, search and rescue, surveillance, and environmental monitoring.
Multi Sensor Railway Track Geometry Surveying System
Linear variable differential transformers (LVDTs) and inclinometers are widely used in many industrial establishments, particularly in the metrology area. These sensors are used by many engineering disciplines because of their high-precision characteristics.
In addition, Global Navigation Satellite System (GNSS) receivers and total stations are widely used in geodesy. Using GNSS receivers is very popular, particularly for navigational purposes. In this paper, a new railway track geometry surveying system, which is designed by integrating the LVDT, inclinometer, GNSS receiver, and total station, is introduced.
This new surveying system is an alternative to classical geodetic measurement methods that are often used for controlling the railway track geometry. Track gauge, super-elevation, gradient, and track axis coordinates, which are railway geometrical parameters, can be instantly determined while making measurements by using the new surveying system
In addition, Global Navigation Satellite System (GNSS) receivers and total stations are widely used in geodesy. Using GNSS receivers is very popular, particularly for navigational purposes. In this paper, a new railway track geometry surveying system, which is designed by integrating the LVDT, inclinometer, GNSS receiver, and total station, is introduced.
This new surveying system is an alternative to classical geodetic measurement methods that are often used for controlling the railway track geometry. Track gauge, super-elevation, gradient, and track axis coordinates, which are railway geometrical parameters, can be instantly determined while making measurements by using the new surveying system
Multi-Platform Wireless Measurement System for Continuous Biomonitoring
This contribution presents new multi-protocol wireless measurement system for continuous biomedical monitoring of human body parameters. The main goal is monitoring of selected physiological processes that might be very useful in health care and monitoring during sport activities.
The monitoring device, based on an on-body sensor, is designed with respect to small size, low power consumption as well as interoperability. Therefore, it is equipped with a microcontroller with RF module for ZigBee PRO or ANT+ networks. Measured data is sent through the wireless network to an acquisition point, which collects the data and transfers it to a database server.
Here, the data is stored and can be accessed remotely via internet. This system is mainly aimed at home health care, so it should be able to communicate with standard personal devices such as cellphone, notebook/netbook, PC, tablet, etc. For this reason, the acquisition point is able to communicate via Bluetooth standard as well as Bluetooth low energy (for future use).
Through this network, user can view live data as well as data stored in the database server. As an example, the system for monitoring of psycho-galvanic reflex of the human skin will be shown. The communication between the acquisition point and sensor is based on ZigBee PRO network and communication between the acquisition point and visualization device uses Bluetooth network, since recently, this is the most common interface used in portable devices.
The monitoring device, based on an on-body sensor, is designed with respect to small size, low power consumption as well as interoperability. Therefore, it is equipped with a microcontroller with RF module for ZigBee PRO or ANT+ networks. Measured data is sent through the wireless network to an acquisition point, which collects the data and transfers it to a database server.
Here, the data is stored and can be accessed remotely via internet. This system is mainly aimed at home health care, so it should be able to communicate with standard personal devices such as cellphone, notebook/netbook, PC, tablet, etc. For this reason, the acquisition point is able to communicate via Bluetooth standard as well as Bluetooth low energy (for future use).
Through this network, user can view live data as well as data stored in the database server. As an example, the system for monitoring of psycho-galvanic reflex of the human skin will be shown. The communication between the acquisition point and sensor is based on ZigBee PRO network and communication between the acquisition point and visualization device uses Bluetooth network, since recently, this is the most common interface used in portable devices.
Multiple Working Mode Control of Door-Opening With a Mobile Modular and Reconfigurable Robot
This paper addresses the problems of opening a door with a modular and reconfigurable robot (MRR) mounted on a wheeled mobile robot platform. The main concern of opening a door is how to prevent the occurrence of large internal forces that arise because of the positioning errors or imprecise modeling of the robot or its environment, specifically, the door parameters.
Unlike previous methods that relied on compliance control, making the control design rather complicated, this paper presents a new concept that utilizes the multiple working modes of the MRR modules. The control design is significantly simplified by switching selected joints of the MRR to work in passive mode during door-opening operation.
As a result, the occurrence of large internal forces is prevented. Different control schemes are used for control of the joint modules in different working modes. For the passive joint modules, a feedforward torque control approach is used to compensate the joint friction to ensure passive motion.
For the active joint modules, a distributed control method based on torque sensing is used to facilitate the control of joint modules working under this mode. To enable autonomous door-opening, an online door parameter estimation algorithm is proposed on the basis of the least squares method, and a path planning algorithm is developed on the basis of Hermite cubic spline functions, with consideration of motion constraints of the mobile MRR. Simulation and experimental results are presented to show the effectiveness of the proposed approach.
Unlike previous methods that relied on compliance control, making the control design rather complicated, this paper presents a new concept that utilizes the multiple working modes of the MRR modules. The control design is significantly simplified by switching selected joints of the MRR to work in passive mode during door-opening operation.
As a result, the occurrence of large internal forces is prevented. Different control schemes are used for control of the joint modules in different working modes. For the passive joint modules, a feedforward torque control approach is used to compensate the joint friction to ensure passive motion.
For the active joint modules, a distributed control method based on torque sensing is used to facilitate the control of joint modules working under this mode. To enable autonomous door-opening, an online door parameter estimation algorithm is proposed on the basis of the least squares method, and a path planning algorithm is developed on the basis of Hermite cubic spline functions, with consideration of motion constraints of the mobile MRR. Simulation and experimental results are presented to show the effectiveness of the proposed approach.
Multi-sensor tracking and lane estimation in highly automated vehicles
Highly automated driving brings the next generation of driver assistance systems for increased safety and comfort. Automated vehicles execute part of the driving tasks whereas the driver is still involved in controlling the vehicle. Higher degrees of automation pose more strict requirements for perception systems in terms of performance and robustness.
The HAVE it EU project investigates the application and validation of highly automated vehicle systems, technologies that are going to have a great impact on transport of the future. The purpose of this study is to examine in detail the problem of multi-sensor fusion for target tracking and road environment perception in an automated vehicle application.
A series of algorithms are described for solving the data association and track estimation problems, both at sensor and central levels. The techniques that are used for multi-sensor lane estimation are also presented. Finally, results from simulated and real-time tests are given to demonstrate the performance of the algorithm.
The HAVE it EU project investigates the application and validation of highly automated vehicle systems, technologies that are going to have a great impact on transport of the future. The purpose of this study is to examine in detail the problem of multi-sensor fusion for target tracking and road environment perception in an automated vehicle application.
A series of algorithms are described for solving the data association and track estimation problems, both at sensor and central levels. The techniques that are used for multi-sensor lane estimation are also presented. Finally, results from simulated and real-time tests are given to demonstrate the performance of the algorithm.
Novel Industrial Wireless Sensor Networks for Machine Condition Monitoring and Fault Diagnosis
This paper proposes a novel industrial wireless sensor network (IWSN) for industrial machine condition monitoring and fault diagnosis. In this paper, the induction motor is taken as an example of monitored industrial equipment due to its wide use in industrial processes. Motor stator current and vibration signals are measured for further processing and analysis.
On-sensor node feature extraction and on-sensor fault diagnosis using neural networks are then investigated to address the tension between the higher system requirements of IWSNs and the resource-constrained characteristics of sensor nodes. A two-step classifier fusion approach using Dempster-Shafer theory is also explored to increase diagnosis result quality. Four motor operating conditions-normal without load, normal with load, loose feet, and mass imbalance-are monitored to evaluate the proposed system.
Experimental results show that, compared with raw data transmission, on-sensor fault diagnosis could reduce payload transmission data by 99%, decrease node energy consumption by 97%, and prolong node lifetime from 106 to 150 h, an increase of 43%. The final fault diagnosis results using the proposed classifier fusion approach give a result certainty of at least 97.5%.
To leverage the advantages of on-sensor fault diagnosis, another system operating mode is explored, which only transmits the fault diagnosis result when a fault happens or at a fixed interval. For this mode, the node lifetime reaches 73 days if sensor nodes transmit diagnosis results once per hour.
On-sensor node feature extraction and on-sensor fault diagnosis using neural networks are then investigated to address the tension between the higher system requirements of IWSNs and the resource-constrained characteristics of sensor nodes. A two-step classifier fusion approach using Dempster-Shafer theory is also explored to increase diagnosis result quality. Four motor operating conditions-normal without load, normal with load, loose feet, and mass imbalance-are monitored to evaluate the proposed system.
Experimental results show that, compared with raw data transmission, on-sensor fault diagnosis could reduce payload transmission data by 99%, decrease node energy consumption by 97%, and prolong node lifetime from 106 to 150 h, an increase of 43%. The final fault diagnosis results using the proposed classifier fusion approach give a result certainty of at least 97.5%.
To leverage the advantages of on-sensor fault diagnosis, another system operating mode is explored, which only transmits the fault diagnosis result when a fault happens or at a fixed interval. For this mode, the node lifetime reaches 73 days if sensor nodes transmit diagnosis results once per hour.
Omega-Shaped Inchworm-Inspired Crawling Robot With Large-Index-and-Pitch (LIP) SMA Spring Actuators
This paper proposes three design concepts for developing a crawling robot inspired by an inchworm, called the Omegabot. First, for locomotion, the robot strides by bending its body into an omega shape; anisotropic friction pads enable the robot to move forward using this simple motion. Second, the robot body is made of a single part but has two four-bar mechanisms and one spherical six-bar mechanism; the mechanisms are 2-D patterned into a single piece of composite and folded to become a robot body that weighs less than 1 g and that can crawl and steer.
This design does not require the assembly of various mechanisms of the body structure, thereby simplifying the fabrication process. Third, a new concept for using a shape-memory alloy (SMA) coil-spring actuator is proposed; the coil spring is designed to have a large spring index and to work over a large pitch-angle range.
This large-index-and-pitch SMA spring actuator cools faster and requires less energy, without compromising the amount of force and displacement that it can produce. Therefore, the frequency and the efficiency of the actuator are improved. A prototype was used to demonstrate that the inchworm-inspired, novel, small-scale, lightweight robot manufactured on a single piece of composite can crawl and steer.
This design does not require the assembly of various mechanisms of the body structure, thereby simplifying the fabrication process. Third, a new concept for using a shape-memory alloy (SMA) coil-spring actuator is proposed; the coil spring is designed to have a large spring index and to work over a large pitch-angle range.
This large-index-and-pitch SMA spring actuator cools faster and requires less energy, without compromising the amount of force and displacement that it can produce. Therefore, the frequency and the efficiency of the actuator are improved. A prototype was used to demonstrate that the inchworm-inspired, novel, small-scale, lightweight robot manufactured on a single piece of composite can crawl and steer.
Online Control of Fuzzy Based Mine Detecting Robot Using Virtual Instrumentation
This paper proposes the design of a micro-controller based fuzzy logic controller for a remote controlled mine detecting robot. In the real time applications the detection and location of bomb is highly essential in the field of defense applications. Considering the value of human life the robot is allowed in the field to detect the bomb.
The mine detecting robot is designed with IR sensors, metal detector and GPS attached to it. The two DC motors are connected with the rear wheels of the robot. Differential drive is used to control the steering angle and the speed of the robot. Differential drive is implemented to control a robot with only two motorized wheels.
The fuzzy logic controller is used for accurate steering angle and the driving speed of the robot. The designed controller has two loops with an Outer Fuzzy Speed Control Loop and an Inner Current Control Loop. Based on the current position and the set speed value, the steering angle and the speed of a mine detecting robot will be controlled.
The software for both the client system and the robot is developed using Data socket protocol in LabVIEW. The motion of the robot is monitored by RF camera. The designed controller was implemented in a PIC 16F877A microcontroller and the results are documented. The mine is detected by metal detector and the location of the mine is known through GPS.
The mine detecting robot is designed with IR sensors, metal detector and GPS attached to it. The two DC motors are connected with the rear wheels of the robot. Differential drive is used to control the steering angle and the speed of the robot. Differential drive is implemented to control a robot with only two motorized wheels.
The fuzzy logic controller is used for accurate steering angle and the driving speed of the robot. The designed controller has two loops with an Outer Fuzzy Speed Control Loop and an Inner Current Control Loop. Based on the current position and the set speed value, the steering angle and the speed of a mine detecting robot will be controlled.
The software for both the client system and the robot is developed using Data socket protocol in LabVIEW. The motion of the robot is monitored by RF camera. The designed controller was implemented in a PIC 16F877A microcontroller and the results are documented. The mine is detected by metal detector and the location of the mine is known through GPS.
Online Sensor Activation for Detectability of Discrete Event Systems
In this paper, we investigate online sensor activation to ensure detectability of discrete event systems. Detectability requires that states of a system can be determined or certain pairs of states can be distinguished by an external observer eventually or periodically.
Since minimal sensor activation policies for detectability may not exist, two new concepts are introduced: 1) k-step distinguishability is introduced for strong detectability and 2) information-preserving is introduced for strong periodic detectability. The online sensor activation is then proposed and is based on the best state estimate available at the time of decision making.
Three algorithms are developed for online sensor activation. The first two algorithms are for strong detectability. They minimize sensor activation while preserving k -step distinguishability. The third algorithm deals with strong periodic detectability. It minimizes sensor activation while preserving state information.
Since minimal sensor activation policies for detectability may not exist, two new concepts are introduced: 1) k-step distinguishability is introduced for strong detectability and 2) information-preserving is introduced for strong periodic detectability. The online sensor activation is then proposed and is based on the best state estimate available at the time of decision making.
Three algorithms are developed for online sensor activation. The first two algorithms are for strong detectability. They minimize sensor activation while preserving k -step distinguishability. The third algorithm deals with strong periodic detectability. It minimizes sensor activation while preserving state information.
Opportunity Estimation for Real-Time Energy Control of Sustainable Manufacturing Systems
Due to the complexity of modern manufacturing systems and the lack of optimal management of energy consumption, the energy efficiency of manufacturing systems in real industrial environment is much lower than designed level, which significantly increases operation cost, impedes company competitiveness in the global market, leads to high carbon dioxide emission, and results in destroyed environment and ecology.
Compared with existing research efforts on energy management of single machine system in the literature, few works have been performed to study the opportunity for energy management of typical manufacturing systems with multiple machines and buffers.
From the point-of-view of sustainability, considering stochastic factor and buffer utilization, this paper investigates the opportunity estimation for real-time energy control of typical multi-machine manufacturing systems without sacrificing system throughput. A numerical case study based on an automotive assembly line is used to illustrate the effectiveness and efficiency of the proposed method.
Compared with existing research efforts on energy management of single machine system in the literature, few works have been performed to study the opportunity for energy management of typical manufacturing systems with multiple machines and buffers.
From the point-of-view of sustainability, considering stochastic factor and buffer utilization, this paper investigates the opportunity estimation for real-time energy control of typical multi-machine manufacturing systems without sacrificing system throughput. A numerical case study based on an automotive assembly line is used to illustrate the effectiveness and efficiency of the proposed method.
Optimal Angular Movement of Laser Beam in SPR using an Embedded Controller
This paper proposes and implements the PIC microcontroller based Surface Plasmon resonance analysis of bio molecular interaction. Surface Plasmon resonance [SPR] has becoming an important optical bio-sensing technology in the areas of medical, biological, biochemistry, pollution detection, aircraft and laboratory research.
The SPR works on the principle of TIR, that when the stepper motor mounted laser beam moving back and forth is focused on the hypotenuse of the gold coated BK-7 prism at an angle greater than the critical angle, hence the laser beam gets reflected back and SPR is generated outward side of the gold coated surface is measured using LDR. The generation of SPR is measured in terms of Refractive index, the refractive index changes with respect to the applied sample (Dielectric loading). Hence even for a small change in molecular interaction can be found using SPR.
The laboratory prototype of PIC microcontroller based SPR was characterized in terms of reflectance and intensity with respect to the incident beam. In the design of instrument PIC 16F73 microcontroller is used to control the laser movement back and forth through stepper motor to increase the fastness and accuracy.
This paper explains and demonstrates the importance of PIC microcontroller in the design and control of the instrument.
The SPR works on the principle of TIR, that when the stepper motor mounted laser beam moving back and forth is focused on the hypotenuse of the gold coated BK-7 prism at an angle greater than the critical angle, hence the laser beam gets reflected back and SPR is generated outward side of the gold coated surface is measured using LDR. The generation of SPR is measured in terms of Refractive index, the refractive index changes with respect to the applied sample (Dielectric loading). Hence even for a small change in molecular interaction can be found using SPR.
The laboratory prototype of PIC microcontroller based SPR was characterized in terms of reflectance and intensity with respect to the incident beam. In the design of instrument PIC 16F73 microcontroller is used to control the laser movement back and forth through stepper motor to increase the fastness and accuracy.
This paper explains and demonstrates the importance of PIC microcontroller in the design and control of the instrument.
Optimal Demand Response Capacity of Automatic Lighting Control
Demand response programs seek to adjust the normal consumption patterns of electric power consumers in response to incentive payments that are offered by utility companies to induce lower consumption at peak hours or when the power system reliability is at risk.
While prior studies have extensively studied the capacity of offering demand response in buildings by controlling the load at air conditioners, water heaters, and various home appliances, they lack to offer methods to also utilize the full demand response capacity of automatic lighting control systems.
Since lighting systems consume a large amount of the total energy used in buildings, addressing this shortcoming is an important research problem. Therefore, in this paper, we propose to take a systematic optimization-based approach to assess demand response capacity of automatic lighting control systems in commercial and office buildings.
While prior studies have extensively studied the capacity of offering demand response in buildings by controlling the load at air conditioners, water heaters, and various home appliances, they lack to offer methods to also utilize the full demand response capacity of automatic lighting control systems.
Since lighting systems consume a large amount of the total energy used in buildings, addressing this shortcoming is an important research problem. Therefore, in this paper, we propose to take a systematic optimization-based approach to assess demand response capacity of automatic lighting control systems in commercial and office buildings.
PDMS Microcantilever based Flow Sensor Integration for Lab-on-a-Chip
In this paper, a simple practical method is presented to fabricate a high aspect ratio horizontal polydimethylsiloxane (PDMS) microcantilever-based flow sensor integrated into a microfluidic device.
A multilayer soft lithography process is developed to fabricate a thin PDMS layer involving the PDMS microcantilever and the microfluidics network. A three-layer fabrication technique is explored for the integration of the microflow meter. The upper and lower PDMS layers are bonded to the thin layer to release the microcantilever for free deflection.
A 3-D finite element analysis is carried out to simulate fluid-structure interaction and estimate cantilever deflection under various flow conditions. The dynamic range of flow rates that is detectable using the flow sensor is assessed by both simulation and experimental methods and compared. Limited by the accuracy of the 1.76- µm resolution of the image acquisition method, the present setup allows for flow rates as low as 35 µL/min to be detected.
This is equal to 0.8-µN resolution in equivalent force at the tip. This flow meter can be integrated into any type of microfluidic-based lab-on-a-chip in which flow measurement is crucial, such as flow cytometry and particle separation applications.
A multilayer soft lithography process is developed to fabricate a thin PDMS layer involving the PDMS microcantilever and the microfluidics network. A three-layer fabrication technique is explored for the integration of the microflow meter. The upper and lower PDMS layers are bonded to the thin layer to release the microcantilever for free deflection.
A 3-D finite element analysis is carried out to simulate fluid-structure interaction and estimate cantilever deflection under various flow conditions. The dynamic range of flow rates that is detectable using the flow sensor is assessed by both simulation and experimental methods and compared. Limited by the accuracy of the 1.76- µm resolution of the image acquisition method, the present setup allows for flow rates as low as 35 µL/min to be detected.
This is equal to 0.8-µN resolution in equivalent force at the tip. This flow meter can be integrated into any type of microfluidic-based lab-on-a-chip in which flow measurement is crucial, such as flow cytometry and particle separation applications.
Performance Metrics of Speed and Separation Monitoring in Shared Workspaces
A set of metrics is proposed that evaluates speed and separation monitoring efficacy in industrial robot environments in terms of the quantification of safety and the effects on productivity.
The collision potential is represented by separation metrics and sensor uncertainty based on perceived noise and bounding region radii. In the event of a bounding region collision between a robot and an obstacle during algorithm evaluation, the severity of the separation failure is reported as a percentage of volume penetration.
The collision potential is represented by separation metrics and sensor uncertainty based on perceived noise and bounding region radii. In the event of a bounding region collision between a robot and an obstacle during algorithm evaluation, the severity of the separation failure is reported as a percentage of volume penetration.
Performance-based Classification of Occupant Posture to Reduce the Risk of Injury in a Collision
This study numerically investigates the development of an adaptive restraint system based on precrash classification of occupant posture. A catalog of restraint laws optimized for nine postures uniformly distributed in posture space is employed.
First, the performance of each restraint law is globally assessed by performing crash simulations in a parametric fashion throughout the entire posture space. Then, restraint systems with catalogs (RSCs) with various numbers of restraint laws are evaluated in terms of injury cost with respect to a restraint system optimized with respect to a nominal posture (RSN). Parametric and nonparametric supervised classifiers are developed for each catalog, and their performances are analyzed.
A catalog with the optimized laws of two out-of-position postures (central and leaning left) showed high performance in terms of reduced injury cost with respect to optimum performance for two distinct validation sets (25.3%/21.6% with statistical classifiers versus 26%/23.8% optimum performance).
The percent injury reduction increased as the number of classes was increased but had diminishing returns going from five to nine restraint laws (28%/24.2% with statistical classifiers versus 30.4%/29.1% optimum reduction).
The results of this study indicated that restraint systems with performance-based classes perform better than restraint systems with region-based classes. Expanding the number of restraint laws and developing new classification algorithms may further improve the performance of adaptive restraint systems.
First, the performance of each restraint law is globally assessed by performing crash simulations in a parametric fashion throughout the entire posture space. Then, restraint systems with catalogs (RSCs) with various numbers of restraint laws are evaluated in terms of injury cost with respect to a restraint system optimized with respect to a nominal posture (RSN). Parametric and nonparametric supervised classifiers are developed for each catalog, and their performances are analyzed.
A catalog with the optimized laws of two out-of-position postures (central and leaning left) showed high performance in terms of reduced injury cost with respect to optimum performance for two distinct validation sets (25.3%/21.6% with statistical classifiers versus 26%/23.8% optimum performance).
The percent injury reduction increased as the number of classes was increased but had diminishing returns going from five to nine restraint laws (28%/24.2% with statistical classifiers versus 30.4%/29.1% optimum reduction).
The results of this study indicated that restraint systems with performance-based classes perform better than restraint systems with region-based classes. Expanding the number of restraint laws and developing new classification algorithms may further improve the performance of adaptive restraint systems.
Pervasive Technology and Public Transport: Opportunities Beyond Telematics
This review of IT-based services offered in public transportation focuses on the passenger's perspective. The authors suggest new directions for future services, stressing the need to develop frameworks for assessing service quality and customer satisfaction.
Photovoltaic Power-Increment-Aided Incremental-Conductance MPPT with Two-Phased Tracking
This paper presents a two-phased tracking that forms a photovoltaic (PV) power-increment-aided incremental-conductance (PI-INC) maximum power point tracking (MPPT) to improve the tracking behavior of the conventional INC MPPT. The PI-INC MPPT performs, using either variable-frequency constant-duty control (VFCD) or constant-frequency variable-duty control (CFVD), with reference to a collectively called threshold-tracking zone (TTZ), beyond which a power-increment (PI) tracking along the Ppv -Vpv curve executes and within which an INC tracking along the Ipv-Vpv curve toward maximum power point (MPP) does.
Delay tracking due to ambiguous conductance-increment detection in the flat portion of the left-hand side of the MPP along the Ipv -Vpv curve will not appear in the PI-INC MPPT by using the PI tracking with clear and correct power-increment detection along the Ppv- Vpv curve.
In addition, the merit of INC MPPT to accurately track against the random solar insolation change still retains in the PI-INC MPPT that uses INC tracking toward MPP along the Ipv -Vpv curve when tracking in the TTZ. Modeling and analysis of two typical PV power converters with VFCD and CFVD controls are addressed for implementing the tracking of the PI-INC MPPT in design and experiment.
The tracking behavior of PI-INC MPPT and the conventional INC MPPT is assessed and compared through elaborate experimental tests
Delay tracking due to ambiguous conductance-increment detection in the flat portion of the left-hand side of the MPP along the Ipv -Vpv curve will not appear in the PI-INC MPPT by using the PI tracking with clear and correct power-increment detection along the Ppv- Vpv curve.
In addition, the merit of INC MPPT to accurately track against the random solar insolation change still retains in the PI-INC MPPT that uses INC tracking toward MPP along the Ipv -Vpv curve when tracking in the TTZ. Modeling and analysis of two typical PV power converters with VFCD and CFVD controls are addressed for implementing the tracking of the PI-INC MPPT in design and experiment.
The tracking behavior of PI-INC MPPT and the conventional INC MPPT is assessed and compared through elaborate experimental tests
Piezoelectric Vibratory-Cantilever Force Sensors and Axial Sensitivity Analysis for Individual Triaxial Tactile Sensing
Vibratory force sensors are fabricated using piezoelectric capacitors on microcantilever structures for triaxial sensitivity by the individual sensor element. The cantilevers have been formed into a 3-D curved shape by controlling residual stress combination of the multilayered structure.
Triaxial tactile sensitivity of the cantilever sensor is analyzed under a tactile load application onto the surface of an elastomer in which the cantilever is embedded, mimicking human skin structure. The cantilever is converse-piezoelectrically excited by an external ac voltage and three resonant modes are developed to detect the applied load vector components by the single sensor element.
Resonant frequency shifts of each mode are investigated upon load applications. The results show that the frequencies vary to the three axial tactile loads independently and they can be superposed with corresponding to the superposition of the load components.
The applied load vectors are estimated by resonant frequencies of the single cantilever sensor with compensating nonlinearities of the sensor response. The estimated error is less than 1.1% to the full scale of the load ±4 kPa.
Triaxial tactile sensitivity of the cantilever sensor is analyzed under a tactile load application onto the surface of an elastomer in which the cantilever is embedded, mimicking human skin structure. The cantilever is converse-piezoelectrically excited by an external ac voltage and three resonant modes are developed to detect the applied load vector components by the single sensor element.
Resonant frequency shifts of each mode are investigated upon load applications. The results show that the frequencies vary to the three axial tactile loads independently and they can be superposed with corresponding to the superposition of the load components.
The applied load vectors are estimated by resonant frequencies of the single cantilever sensor with compensating nonlinearities of the sensor response. The estimated error is less than 1.1% to the full scale of the load ±4 kPa.
PIR sensor based Lighting Device with Ultra-Low Standby Power Consumption
In this paper we present a way to reduce the standby power consumption of a PIR-sensor-based lighting device. Generally, although a PIR-sensor-based lighting device will turn on when motion is detected and turn off when the motion is no longer present, this device still consumes 1-3 W of power when the lamp is off.
In this design the device consumes 0.004 W when the light is turned off, and it is not only easy to set up but also inexpensive. Our circuit supplies the lamp with power when motion is detected; when the motion disappears it turns the lamp off, and the electric power is shut off to reduce the standby power.
We use an MCU receiving signals from a PIR sensor which detects any individual approaching the device. The MCU controls the SSR On/Off when used as a light switch for shutting off the standby power.
The MCU monitoring program provides automatic detection of any individual by means of the PIR sensor. The MCU has internal modules to simplify the hardware circuit design.
In this design the device consumes 0.004 W when the light is turned off, and it is not only easy to set up but also inexpensive. Our circuit supplies the lamp with power when motion is detected; when the motion disappears it turns the lamp off, and the electric power is shut off to reduce the standby power.
We use an MCU receiving signals from a PIR sensor which detects any individual approaching the device. The MCU controls the SSR On/Off when used as a light switch for shutting off the standby power.
The MCU monitoring program provides automatic detection of any individual by means of the PIR sensor. The MCU has internal modules to simplify the hardware circuit design.
Portable Camera-based Assistive Text and Product Label Reading from Hand-Held Objects for Blind Persons
We propose a camera-based assistive text reading framework to help blind persons read text labels and product packaging from hand-held objects in their daily lives. To isolate the object from cluttered backgrounds or other surrounding objects in the camera view, we first propose an efficient and effective motion-based method to define a region of interest (ROI) in the video by asking the user to shake the object.
This method extracts moving object region by a mixture-of-Gaussians-based background subtraction method. In the extracted ROI, text localization and recognition are conducted to acquire text information. To automatically localize the text regions from the object ROI, we propose a novel text localization algorithm by learning gradient features of stroke orientations and distributions of edge pixels in an Adaboost model. Text characters in the localized text regions are then binarized and recognized by off-the-shelf optical character recognition software.
The recognized text codes are output to blind users in speech. Performance of the proposed text localization algorithm is quantitatively evaluated on ICDAR-2003 and ICDAR-2011 Robust Reading Datasets. Experimental results demonstrate that our algorithm achieves the state of the arts.
The proof-of-concept prototype is also evaluated on a dataset collected using ten blind persons to evaluate the effectiveness of the system's hardware. We explore user interface issues and assess robustness of the algorithm in extracting and reading text from different objects with complex backgrounds.
This method extracts moving object region by a mixture-of-Gaussians-based background subtraction method. In the extracted ROI, text localization and recognition are conducted to acquire text information. To automatically localize the text regions from the object ROI, we propose a novel text localization algorithm by learning gradient features of stroke orientations and distributions of edge pixels in an Adaboost model. Text characters in the localized text regions are then binarized and recognized by off-the-shelf optical character recognition software.
The recognized text codes are output to blind users in speech. Performance of the proposed text localization algorithm is quantitatively evaluated on ICDAR-2003 and ICDAR-2011 Robust Reading Datasets. Experimental results demonstrate that our algorithm achieves the state of the arts.
The proof-of-concept prototype is also evaluated on a dataset collected using ten blind persons to evaluate the effectiveness of the system's hardware. We explore user interface issues and assess robustness of the algorithm in extracting and reading text from different objects with complex backgrounds.
Predictive Prevention of Loss Of Vehicle Control for Roadway Departure Avoidance
In this paper, we investigate predictive approaches to the problem of roadway departure prevention via automated steering and braking. We assume a sensing infrastructure detecting road geometry and consider a two-layer accident avoidance framework consisting of a threat assessment and an intervention layer.
A novel active safety function for prevention of loss of vehicle control is proposed and implemented using the considered accident avoidance framework. Simulation and experimental results are presented, showing that the proposed approach effectively exploits road preview information to prevent the vehicle from operating in regions of the state space where standard electronic stability control systems are normally activated
A novel active safety function for prevention of loss of vehicle control is proposed and implemented using the considered accident avoidance framework. Simulation and experimental results are presented, showing that the proposed approach effectively exploits road preview information to prevent the vehicle from operating in regions of the state space where standard electronic stability control systems are normally activated
Preemptive scheduling execution in Real Time OS for Multilayer security system
Multicore virtualization can offer significant benefits to embedded avionics systems with regard to enabling mixed real-time and guest operating system interoperability, legacy code migration, and hardware consolidation. Virtualization enabled architectures have evolved from a traditional Hypervisor Monolithic Model (VmWare and VirtualLogix), to a Hypervisor Console Guest Monolithic Model (Xen), and now to a High Assurance Microkernel Hypervisor RTOS Model.
The ability to consolidate multiple legacy Single Board Computers (SBCs) with various guest operating systems and applications into a multicore, virtualized SBC is a critical enabler to next generation avionics. This paper describes an initial feasibility assessment toward applying the Microkernel Hypervisor RTOS Virtual Machine (VM) architecture to enable virtualization for a representative set of avionics applications requiring multiple guest OS environments.
The specific notional configuration included: legacy application execution on a legacy RTOS guest OS in VM1, newer application execution on a more recently released level of RTOS on VM2, safety critical applications execution on an ARINC 653 OS on VM3, Global Information Grid (GIG) applications execution on a Linux guest OS on VM4, and MILS/MLS application execution on a high assurance OS on VM5, all executing on a Microkernel Hypervisor RTOS within a Multicore (X86 or Power PC) with hardware-based virtualization support.
The paper identifies the current system design issues, limitations/restrictions, and feasibility of applying representative products in this representative hybrid legacy/next generation environment. The system design challenges identified included: 1.) selection of communication mechanisms and scheduling for mixed operating system environments, 2.) addressing current limitations/restrictions of current vendor products with regard to multicore, 3.) properly scheduling the infrastructure to meet the safety and security requirements, 4.) inc- - orporating extensions for MultiLevel Security (MLS) components for networked GIG and local connectivity, and 5.) consolidating I/O components without compromising safety, security, and redundancy considerations.
The ability to consolidate multiple legacy Single Board Computers (SBCs) with various guest operating systems and applications into a multicore, virtualized SBC is a critical enabler to next generation avionics. This paper describes an initial feasibility assessment toward applying the Microkernel Hypervisor RTOS Virtual Machine (VM) architecture to enable virtualization for a representative set of avionics applications requiring multiple guest OS environments.
The specific notional configuration included: legacy application execution on a legacy RTOS guest OS in VM1, newer application execution on a more recently released level of RTOS on VM2, safety critical applications execution on an ARINC 653 OS on VM3, Global Information Grid (GIG) applications execution on a Linux guest OS on VM4, and MILS/MLS application execution on a high assurance OS on VM5, all executing on a Microkernel Hypervisor RTOS within a Multicore (X86 or Power PC) with hardware-based virtualization support.
The paper identifies the current system design issues, limitations/restrictions, and feasibility of applying representative products in this representative hybrid legacy/next generation environment. The system design challenges identified included: 1.) selection of communication mechanisms and scheduling for mixed operating system environments, 2.) addressing current limitations/restrictions of current vendor products with regard to multicore, 3.) properly scheduling the infrastructure to meet the safety and security requirements, 4.) inc- - orporating extensions for MultiLevel Security (MLS) components for networked GIG and local connectivity, and 5.) consolidating I/O components without compromising safety, security, and redundancy considerations.
Prioritized Vehicle to vehicle communication using Wireless CAN Network with Graphical User Interface (GUI) System
Design of Vehicular monitoring and tracking system based on ARM using GSM and GPM is proposed. The vehicular module is used to track, monitor, and surveillance and finds the accident spot and intimate to the monitoring station.
The proposed design provides information regarding vehicle Identity, speed, and position on real time basis. This information are collected by the ARM7 TDMI-S core processor LPC2148 by using different module and dispatch it to the monitoring station where it stores the information in database and display it on graphical user interface (GUI) that is user friendly. GUI is built on Microsoft Visual Studio 2010. This design provides information in real time using µc/OS-II.
The proposed design provides information regarding vehicle Identity, speed, and position on real time basis. This information are collected by the ARM7 TDMI-S core processor LPC2148 by using different module and dispatch it to the monitoring station where it stores the information in database and display it on graphical user interface (GUI) that is user friendly. GUI is built on Microsoft Visual Studio 2010. This design provides information in real time using µc/OS-II.
Prototype of a fingerprint based licensing system for driving
To prevent non-licensees from driving and therefore causing accidents, a new system is proposed. An important and very reliable human identification method is fingerprint identification. Fingerprint identification is one of the most popular and reliable personal biometric identification methods.
The proposed system consists of a smart card capable of storing the fingerprint of particular person. While issuing the license, the specific person's fingerprint is to be stored in the card. Vehicles such as cars, bikes etc should have a card reader capable of reading the particular license. The same automobile should have the facility of fingerprint reader device.
A person, who wishes to drive the vehicle, should insert the card (license) in the vehicle and then swipe his/her finger. If the finger print stored in the card and fingerprint swiped in the device matches, he/she can proceed for ignition, otherwise ignition will not work. Moreover, the seat belt detector verifies and then prompts the user to wear the seat belt before driving. This increases the security of vehicles and also ensures safe driving by preventing accidents.
The proposed system consists of a smart card capable of storing the fingerprint of particular person. While issuing the license, the specific person's fingerprint is to be stored in the card. Vehicles such as cars, bikes etc should have a card reader capable of reading the particular license. The same automobile should have the facility of fingerprint reader device.
A person, who wishes to drive the vehicle, should insert the card (license) in the vehicle and then swipe his/her finger. If the finger print stored in the card and fingerprint swiped in the device matches, he/she can proceed for ignition, otherwise ignition will not work. Moreover, the seat belt detector verifies and then prompts the user to wear the seat belt before driving. This increases the security of vehicles and also ensures safe driving by preventing accidents.
Prototype of an Underground Multi-Storied Automated Car Parking System
This work proposes to develop and implement a prototype model of an efficient unmanned car parking system using microcontroller. Model developed for underground car parking with multiple floors, prevents the usage of the parking space at ground level. Entire process was automated so that it reduces the time wasted by a person to park a car.
This model uses two circular floors, with six car-parking slots in each floor. This mechanism has centre primary shaft holding a lift to transport the vehicle to its appropriate parking slot. Various sensors, motors and software were used to detect and transport the car to its allocated parking slot.
Hence, this system provides a closed loop control, making it an efficient, accurate, secure and a convenient method proposed for parking cars in both commercial and residential areas.
This model uses two circular floors, with six car-parking slots in each floor. This mechanism has centre primary shaft holding a lift to transport the vehicle to its appropriate parking slot. Various sensors, motors and software were used to detect and transport the car to its allocated parking slot.
Hence, this system provides a closed loop control, making it an efficient, accurate, secure and a convenient method proposed for parking cars in both commercial and residential areas.
Prototypes of Opportunistic Wireless Sensor Networks Supporting Indoor Air Quality Monitoring
In this demonstration proposal we describe a prototype of a Wireless Sensor Network (WSN) for monitoring thWater environment monitoring system based on wireless sensor networks (WSNs) consists of three parts: data monitoring nodes, date video base station and remote monitoring center.
For the sake of realizing to monitor large range waters such as reservoir, wetland, lake, river and ocean etc, the monitoring system has the function of perception, acquisition, processing and transmission for video-information in key areas and various water environment parameters, such as water temperature, PH, turbidity, electric conductivity, dissolved oxygen and so on. As the gateway between those data monitoring nodes and CDMA network, the data video base station is communication center in the monitoring network.
Based on ARM-DSP double processors architecture, the date video base station for water environment monitoring is studied and its software and hardware is designed in this paper. Moreover, by means of ZigBee and CDMA wireless transmission technology, the base station realizes data bidirectional communication between the sensor networks and the remote monitoring center.
It well meets the need of remote real time water environment monitoring system and also has wide application prospect in industrial control, smart home, medical telemetry and intelligent traffic, etc.
For the sake of realizing to monitor large range waters such as reservoir, wetland, lake, river and ocean etc, the monitoring system has the function of perception, acquisition, processing and transmission for video-information in key areas and various water environment parameters, such as water temperature, PH, turbidity, electric conductivity, dissolved oxygen and so on. As the gateway between those data monitoring nodes and CDMA network, the data video base station is communication center in the monitoring network.
Based on ARM-DSP double processors architecture, the date video base station for water environment monitoring is studied and its software and hardware is designed in this paper. Moreover, by means of ZigBee and CDMA wireless transmission technology, the base station realizes data bidirectional communication between the sensor networks and the remote monitoring center.
It well meets the need of remote real time water environment monitoring system and also has wide application prospect in industrial control, smart home, medical telemetry and intelligent traffic, etc.
Real Life Applicable Fall Detection System Based on Wireless Body Area network
Real-time health monitoring with wearable sensors is an active area of research. In this domain, observing the physical condition of elderly people or patients in personal environments such as home, office, and restroom has special significance because they might be unassisted in these locations.
The elderly people have limited physical abilities and are more vulnerable to serious physical damages even with small accidents, e.g. fall. The falls are unpredictable and unavoidable. In case of a fall, early detection and prompt notification to emergency services is essential for quick recovery. However, the existing fall detection devices are bulky and uncomfortable to wear. Also, detection system using the devices requires the higher computation overhead to detect falls from activities of daily living (ADL).
In this paper, we propose a new fall detection system using one sensor node which can be worn as a necklace to provide both the comfortable wearing and low computation overhead. The proposed necklace-shaped sensor node includes tri-axial accelerometer and gyroscope sensors to classify the behaviour and posture of the detection subject.
The simulated experimental results performed 5 fall scenarios 50 times by 5 persons show that our proposed detection approach can successfully distinguish between ADL and fall, with sensitivities greater than 80% and specificities of 100%.
The elderly people have limited physical abilities and are more vulnerable to serious physical damages even with small accidents, e.g. fall. The falls are unpredictable and unavoidable. In case of a fall, early detection and prompt notification to emergency services is essential for quick recovery. However, the existing fall detection devices are bulky and uncomfortable to wear. Also, detection system using the devices requires the higher computation overhead to detect falls from activities of daily living (ADL).
In this paper, we propose a new fall detection system using one sensor node which can be worn as a necklace to provide both the comfortable wearing and low computation overhead. The proposed necklace-shaped sensor node includes tri-axial accelerometer and gyroscope sensors to classify the behaviour and posture of the detection subject.
The simulated experimental results performed 5 fall scenarios 50 times by 5 persons show that our proposed detection approach can successfully distinguish between ADL and fall, with sensitivities greater than 80% and specificities of 100%.
Real Time hand gesture Detection and recognition Using Bag-Of-Features and Support Vector Machine Techniques
This paper presents a novel and real-time system for interaction with an application or video game via hand gestures. Our system includes detecting and tracking bare hand in cluttered background using skin detection and hand posture contour comparison algorithm after face subtraction, recognizing hand gestures via bag-of-features and multiclass support vector machine (SVM) and building a grammar that generates gesture commands to control an application.
In the training stage, after extracting the keypoints for every training image using the scale invariance feature transform (SIFT), a vector quantization technique will map keypoints from every training image into a unified dimensional histogram vector (bag-of-words) after K-means clustering. This histogram is treated as an input vector for a multiclass SVM to build the training classifier.
In the testing stage, for every frame captured from a webcam, the hand is detected using our algorithm, then, the keypoints are extracted for every small image that contains the detected hand gesture only and fed into the cluster model to map them into a bag-of-words vector, which is finally fed into the multiclass SVM training classifier to recognize the hand gesture.
In the training stage, after extracting the keypoints for every training image using the scale invariance feature transform (SIFT), a vector quantization technique will map keypoints from every training image into a unified dimensional histogram vector (bag-of-words) after K-means clustering. This histogram is treated as an input vector for a multiclass SVM to build the training classifier.
In the testing stage, for every frame captured from a webcam, the hand is detected using our algorithm, then, the keypoints are extracted for every small image that contains the detected hand gesture only and fed into the cluster model to map them into a bag-of-words vector, which is finally fed into the multiclass SVM training classifier to recognize the hand gesture.
Real Time Operating System based environmental data capturing and analysis
Increased railway patronage worldwide is putting pressure on rolling stock and infrastructure to operate at higher capacity and with improved punctuality. Condition monitoring is seen as a contributing factor in enabling this and is highlighted here in the context of rolling stock being procured with high capacity data buses, multiple sensors and centralised control.
This therefore leaves scope for advanced computational diagnostic concepts. The rail vehicle bogie and associated wheelsets are one of the largest and most costly areas of maintenance on rolling stock and presented here is a potential method for real time estimation of wheel-rail contact wear to move this currently scheduled based assessment to condition based assessment.
This technique utilises recursive ‘grey box’ least squares system identification, used in a piecewise linear manner, to capture the strongly discontinuous nonlinear nature of the wheel-rail geometry.
This therefore leaves scope for advanced computational diagnostic concepts. The rail vehicle bogie and associated wheelsets are one of the largest and most costly areas of maintenance on rolling stock and presented here is a potential method for real time estimation of wheel-rail contact wear to move this currently scheduled based assessment to condition based assessment.
This technique utilises recursive ‘grey box’ least squares system identification, used in a piecewise linear manner, to capture the strongly discontinuous nonlinear nature of the wheel-rail geometry.
Reconfigurable Computing in Next-Generation Automotive Networks
Modern vehicles incorporate a significant amount of computation, which has led to an increase in the number of computational nodes and the need for faster in-vehicle networks. Functions range from noncritical control of electric windows, through critical drive-by-wire systems, to entertainment applications; as more systems are automated, this variety and number will continue to increase.
Accommodating the varying computational and communication requirements of such a diverse range of functions requires flexible networks and embedded computing devices. As the number of electronic control units (ECUs) increases, power and efficiency become more important, more so in next-generation electric vehicles.
Moreover, predictability and isolation of safety-critical functions are nontrivial challenges when aggregating multiple functions onto fewer nodes. Reconfigurable computing can play a key role in addressing these challenges, providing both static and dynamic flexibility, with high computational capabilities, at lower power consumption.
Reconfigurable hardware also provides resources and methods to address deterministic requirements, reliability and isolation of aggregated functions. This letter presents some initial research on the place of reconfigurable computing in future vehicles.
Accommodating the varying computational and communication requirements of such a diverse range of functions requires flexible networks and embedded computing devices. As the number of electronic control units (ECUs) increases, power and efficiency become more important, more so in next-generation electric vehicles.
Moreover, predictability and isolation of safety-critical functions are nontrivial challenges when aggregating multiple functions onto fewer nodes. Reconfigurable computing can play a key role in addressing these challenges, providing both static and dynamic flexibility, with high computational capabilities, at lower power consumption.
Reconfigurable hardware also provides resources and methods to address deterministic requirements, reliability and isolation of aggregated functions. This letter presents some initial research on the place of reconfigurable computing in future vehicles.
Reliability Guarantees in Automata-Based Scheduling for Embedded Control Software
Automata-based scheduling is a recent technique for online scheduling of software control components in embedded systems. This letter studies one important aspect of automata-based scheduling that has not been studied in the past, namely resilience to faults.
The goal of the proposed technique is to create an automaton that recommends the scheduling patterns that are admissible with respect to control performance requirements, when the state of the system has been mutated by faults. The problem has been formulated as a game between the scheduler and the (possibly faulty) system, where a winning strategy of the scheduler prevents the system from reaching bad states forever.
We present a method for analyzing the structure of the game and extracting an automaton that captures the winning strategies of the scheduler, namely the automaton to be used for automata-based scheduling.
The goal of the proposed technique is to create an automaton that recommends the scheduling patterns that are admissible with respect to control performance requirements, when the state of the system has been mutated by faults. The problem has been formulated as a game between the scheduler and the (possibly faulty) system, where a winning strategy of the scheduler prevents the system from reaching bad states forever.
We present a method for analyzing the structure of the game and extracting an automaton that captures the winning strategies of the scheduler, namely the automaton to be used for automata-based scheduling.
Remote control system of high efficiency and intelligent street lighting using Zigbee network of devices and sensors
The proposed remote-control system can optimize management and efficiency of street lighting systems. It uses ZigBee-based wireless devices which enable more efficient street lamp-system management, thanks to an advanced interface and control architecture.
It uses a sensor combination to control and guarantee the desired system parameters; the information is transferred point by point using ZigBee transmitters and receivers and is sent to a control terminal used to check the state of the street lamps and to take appropriate measures in case of failure
It uses a sensor combination to control and guarantee the desired system parameters; the information is transferred point by point using ZigBee transmitters and receivers and is sent to a control terminal used to check the state of the street lamps and to take appropriate measures in case of failure
Requirement-Based Bidding Language for Agent-Based Scheduling
This paper presents a requirement-based bidding language for agent-based scheduling. The language allows agents to attach their valuations directly to scheduling performance requirements.
Compared with general bidding languages, the proposed one reduces agents' valuation and system's communication complexities. In addition, it results in efficient winner determination problem models.
Experimental results show that the requirement-based language exhibits superior winner determination performance in terms of problem-solving speed and scalability.
Compared with general bidding languages, the proposed one reduces agents' valuation and system's communication complexities. In addition, it results in efficient winner determination problem models.
Experimental results show that the requirement-based language exhibits superior winner determination performance in terms of problem-solving speed and scalability.
Research on Elevator Intelligent-Card Control System based on Can Bus
Now the existing elevator control system cannot meet the requirement of safety and energy saving management. So this paper researches the elevator intelligent-card control system based on CAN bus, involving computer technology, network technology, IC card inductive technology and so on.
The elevator energy saving management and the visitor registration problems are solved from the technical level. The powerful software platform for property management is developed, which has high degree of technical difficulty and complexity.
Compared with the traditional elevator management method, it is a great technical progress, and is a great accumulation for developing similar application system.
The elevator energy saving management and the visitor registration problems are solved from the technical level. The powerful software platform for property management is developed, which has high degree of technical difficulty and complexity.
Compared with the traditional elevator management method, it is a great technical progress, and is a great accumulation for developing similar application system.
Research on the Tele-Operating Robot System With Tele-Presence
Armed at solving the problems appeared in researching servo control system of bomb-disposed robot at a distance, adopting Zhangpsilas image calibrating method, accomplished the both eyes stereo-identity mission. Having found the geometry solution for every manipulator joint angle, avoided finding the solution of inverse process of the kinematics.
Have applied the RTW code to generate a software , built the target system of xPC Target, used data transfer station, realized parallel working between master control PC machine and embedded computer PC104, structured bomb-disposed robot servo control system at a distance. Stereo vision identification system is used, producing weight and clamping width estimation in the image of the suspicious explosive object.
According to the monochrome gray scale difference in rows of image matrix of pre explosive object, the estimation way of explosive object surface roughness is gained. Meanwhile, current servo-control needed by completed flexible control strategy of explosive handling robot's paw has been constructed. The project is feasible proved by my experiment.
Have applied the RTW code to generate a software , built the target system of xPC Target, used data transfer station, realized parallel working between master control PC machine and embedded computer PC104, structured bomb-disposed robot servo control system at a distance. Stereo vision identification system is used, producing weight and clamping width estimation in the image of the suspicious explosive object.
According to the monochrome gray scale difference in rows of image matrix of pre explosive object, the estimation way of explosive object surface roughness is gained. Meanwhile, current servo-control needed by completed flexible control strategy of explosive handling robot's paw has been constructed. The project is feasible proved by my experiment.
Research on water saving irrigation automation control system based on internet on things
To improve irrigation water use efficiency, reduce cost of irrigation water, this paper discussed the design of wireless sensor network and Internet technology of farmland automatic irrigation control method. Emphasis on an analysis of the routing protocol of sensor network nodes to achieve the system hardware and software design, middleware, and applications such as mobile phone or wireless PDA of internet of things,will constitute a variety of sensors intelligent network, thus enhancing the overall automation system and monitoring levels.
The final analysis of the network in the Internet based on the agricultural plants of farmland water-saving irrigation system integrated approach. User use mobile phones or wireless PDA can easily soil moisture content of online monitoring and control to realize the irrigation automation.
Application results show that system through the embedded control technology complete intelligent irrigation, improve the agricultural irrigation water use efficiency and irrigation system automatization is generally low status, can well realize water saving.
The final analysis of the network in the Internet based on the agricultural plants of farmland water-saving irrigation system integrated approach. User use mobile phones or wireless PDA can easily soil moisture content of online monitoring and control to realize the irrigation automation.
Application results show that system through the embedded control technology complete intelligent irrigation, improve the agricultural irrigation water use efficiency and irrigation system automatization is generally low status, can well realize water saving.
RFID based Digital Content Copy Protection System in Movie and Audio Rental Agency
As media rental markets have expanded, a secure digital content protection system is urgently demanded. It is true that digital right management (DRM) has made tremendous progress in fighting piracy, but the pirated contents are still rampant due to the weakness of DRM systems.
Because they are incapable of controlling external pirate action like analog/digital bus tampering.In this paper, we propose a novel approach using RFID (Radio Frequency Identification) technology and cryptography algorithm to provide end-to-end protection.
Because they are incapable of controlling external pirate action like analog/digital bus tampering.In this paper, we propose a novel approach using RFID (Radio Frequency Identification) technology and cryptography algorithm to provide end-to-end protection.
RFID based Location System for Forest Search and Rescue Missions
This paper presents the framework of an RFID-based rescue robot for missing people in forest environment. The three main design considerations include the reliability, the cost, and the environmental sustainability. For that, the paper analyzes different outdoor location technologies that can be used for this task, namely GPS, WiMAX and RFID. Former research in mobile robots based on GPS and WiMAX has resulted in high costs systems while RFID offers a lower cost alternative.
The aim of this work is to provide an already existing mobile robot with RFID technology. Moreover, to overcome the inability of current rescue robots to detect human presence, the addition of an Infrared camera with thermal sensors is discussed. Finally, in order to optimize the energy management and to increase the autonomy of the rescue robot, the paper presents a power supply solution using solar energy.
The aim of this work is to provide an already existing mobile robot with RFID technology. Moreover, to overcome the inability of current rescue robots to detect human presence, the addition of an Infrared camera with thermal sensors is discussed. Finally, in order to optimize the energy management and to increase the autonomy of the rescue robot, the paper presents a power supply solution using solar energy.
RFID based Tracking System Preventing Trees Extinction and Deforestation
This paper describes the design of a radio frequency identification system that we called TreesRFID Tracking System (TRTS). This suggested study develops a system that would enable the detection and identification of trees illegal logging cases and hence preventing risks of species distinction and deforestation threats.
The TRTS consists of RFID passive tags (static tags) fitted in trees and serving as unique identity for each tree, handheld readers (moving devices) with a suitable readable range and embedded circular polarization antenna. These readers would be held by forest officers and the data read from the tags would be accessible through the readers thanks to a visualization software that would analyze and process the data received.
The database that saves all the readings and user interface and enables access to that data is located at the server side of the system. Communication between the tag readers and the server side is done through 3G connectivity enabled at the handheld reader device. An example of this suggested study practicality is the forests in Ifrane region of Atlas Mountains which are well known for the cedar species that are constantly subject to illegal extracting and thus are threatened by extinction. Moreover there has been no suggested method to improve their management process. Here is where our RFID system comes to play.
The TRTS consists of RFID passive tags (static tags) fitted in trees and serving as unique identity for each tree, handheld readers (moving devices) with a suitable readable range and embedded circular polarization antenna. These readers would be held by forest officers and the data read from the tags would be accessible through the readers thanks to a visualization software that would analyze and process the data received.
The database that saves all the readings and user interface and enables access to that data is located at the server side of the system. Communication between the tag readers and the server side is done through 3G connectivity enabled at the handheld reader device. An example of this suggested study practicality is the forests in Ifrane region of Atlas Mountains which are well known for the cedar species that are constantly subject to illegal extracting and thus are threatened by extinction. Moreover there has been no suggested method to improve their management process. Here is where our RFID system comes to play.
Robot Navigation System Using RFID and Sensors
This paper proposes an efficient method for localization and pose estimation for mobile robot navigation using passive radio-frequency identification (RFID). We assume that the robot is able to identify IC tags and measure the robot's pose based on the relation between the previous and current location according to the IC tags.
However, there arises the problem of uncertainty of location due to the nature of the antenna and IC tags. In other words, an error is always present which is relative to the sensing area of the antenna. Many researches have used external sensors in order to reduce the location errors, with few researches presented involving purely RFID driven systems.
Our proposed algorithm that uses only passive RFID is able to estimate the robot's location and orientation more precisely by using trigonometric functions and the IC tags' Cartesian coordinates in a regular gridlike pattern. The experimental results show that the proposed method effectively estimates both the location and the pose of a mobile robot during navigation
However, there arises the problem of uncertainty of location due to the nature of the antenna and IC tags. In other words, an error is always present which is relative to the sensing area of the antenna. Many researches have used external sensors in order to reduce the location errors, with few researches presented involving purely RFID driven systems.
Our proposed algorithm that uses only passive RFID is able to estimate the robot's location and orientation more precisely by using trigonometric functions and the IC tags' Cartesian coordinates in a regular gridlike pattern. The experimental results show that the proposed method effectively estimates both the location and the pose of a mobile robot during navigation
Robust Adaptive Controller for a Tractor–Trailer Mobile Robot
A tractor--trailer wheeled robot (TTWR) is a kind of modular robotic system that consists of a tractor template attached with a single or multiple trailers, and hence it is a nonlinear and underactuated system subjected to nonholonomic constraints. Tracking control of such a complicated system is a challenging problem, and that is the focus of this paper. To this end, first dynamics model of a TTWR is developed.
Next, feasible reference trajectories are generated to define a trajectory tracking problem. Then, a Lyapunov kinematic control law is elaborated to stabilize tracking errors. Subsequently, a feedback linearizing dynamic controller (FLDC) is designed to generate actuator torques. In a wheeled mobile robot (WMR), like most of real engineering applications, it is impossible to obtain an exact dynamics model due to various unknown, or unpredictable and irregular features. Therefore, the robustness of controllers to overcome uncertainties and external disturbances is necessary.
So, a robust adaptive feedback linearizing dynamic controller (RAFLDC) is proposed to control the system using estimated upper-bounds of uncertainties. The stability of the control algorithm is verified using the Lyapunov method. Robustness and effectiveness of the proposed controller, and comparison of results for RAFLDC and FLDC algorithms, is investigated using both simulation studies and experimental implementations, and obtained results will be discussed.
Next, feasible reference trajectories are generated to define a trajectory tracking problem. Then, a Lyapunov kinematic control law is elaborated to stabilize tracking errors. Subsequently, a feedback linearizing dynamic controller (FLDC) is designed to generate actuator torques. In a wheeled mobile robot (WMR), like most of real engineering applications, it is impossible to obtain an exact dynamics model due to various unknown, or unpredictable and irregular features. Therefore, the robustness of controllers to overcome uncertainties and external disturbances is necessary.
So, a robust adaptive feedback linearizing dynamic controller (RAFLDC) is proposed to control the system using estimated upper-bounds of uncertainties. The stability of the control algorithm is verified using the Lyapunov method. Robustness and effectiveness of the proposed controller, and comparison of results for RAFLDC and FLDC algorithms, is investigated using both simulation studies and experimental implementations, and obtained results will be discussed.
Robust Part based Hand Gesture Recognition based On Finger-Earth Mover’s Distance
The recently developed depth sensors, e.g., the Kinect sensor, have provided new opportunities for human-computer interaction (HCI). Although great progress has been made by leveraging the Kinect sensor, e.g., in human body tracking, face recognition and human action recognition, robust hand gesture recognition remains an open problem.
Compared to the entire human body, the hand is a smaller object with more complex articulations and more easily affected by segmentation errors. It is thus a very challenging problem to recognize hand gestures. This paper focuses on building a robust part-based hand gesture recognition system using Kinect sensor. To handle the noisy hand shapes obtained from the Kinect sensor, we propose a novel distance metric, Finger-Earth Mover's Distance (FEMD), to measure the dissimilarity between hand shapes.
As it only matches the finger parts while not the whole hand, it can better distinguish the hand gestures of slight differences. The extensive experiments demonstrate that our hand gesture recognition system is accurate (a 93.2% mean accuracy on a challenging 10-gesture dataset), efficient (average 0.0750 s per frame), robust to hand articulations, distortions and orientation or scale changes, and can work in uncontrolled environments (cluttered backgrounds and lighting conditions). The superiority of our system is further demonstrated in two real-life HCI applications.
Compared to the entire human body, the hand is a smaller object with more complex articulations and more easily affected by segmentation errors. It is thus a very challenging problem to recognize hand gestures. This paper focuses on building a robust part-based hand gesture recognition system using Kinect sensor. To handle the noisy hand shapes obtained from the Kinect sensor, we propose a novel distance metric, Finger-Earth Mover's Distance (FEMD), to measure the dissimilarity between hand shapes.
As it only matches the finger parts while not the whole hand, it can better distinguish the hand gestures of slight differences. The extensive experiments demonstrate that our hand gesture recognition system is accurate (a 93.2% mean accuracy on a challenging 10-gesture dataset), efficient (average 0.0750 s per frame), robust to hand articulations, distortions and orientation or scale changes, and can work in uncontrolled environments (cluttered backgrounds and lighting conditions). The superiority of our system is further demonstrated in two real-life HCI applications.
RT-Linux priority reversal and priority inheritance mechanism
RT-Linux is a kind of embedded Linux, its real time performance is relative high among numerous kind of embedded Linux, but it requires the operation system have high real time performance and using priority inheritance protocol to solve the priority reverse problem in RT-Linux.
In order to trace the system roundly, a kernel trace tool is designed, and used this tool to test the improvement. The test results show that the work eliminated the priority reverse problem, and advanced the real time performance of RT-Linux.
In order to trace the system roundly, a kernel trace tool is designed, and used this tool to test the improvement. The test results show that the work eliminated the priority reverse problem, and advanced the real time performance of RT-Linux.
Safe Maritime Autonomous Navigation With COLREGS, using Velocity Obstacles
This paper presents an autonomous motion planning algorithm for unmanned surface vehicles (USVs) to navigate safely in dynamic, cluttered environments. The algorithm not only addresses hazard avoidance (HA) for stationary and moving hazards, but also applies the International Regulations for Preventing Collisions at Sea (known as COLREGS, for COLlision REGulationS).
The COLREGS rules specify, for example, which vessel is responsible for giving way to the other and to which side of the “stand-on” vessel to maneuver. Three primary COLREGS rules are considered in this paper: crossing, overtaking, and head-on situations. For autonomous USVs to be safely deployed in environments with other traffic boats, it is imperative that the USV's navigation algorithm obeys COLREGS. Furthermore, when other boats disregard their responsibility under COLREGS, the USV must fall back to its HA algorithms to prevent a collision.
The proposed approach is based on velocity obstacles (VO) method, which generates a cone-shaped obstacle in the velocity space. Because VOs also specify on which side of the obstacle the vehicle will pass during the avoidance maneuver, COLREGS are encoded in the velocity space in a natural way. Results from several experiments involving up to four vessels are presented, in what we believe is the first on-water demonstration of autonomous COLREGS maneuvers without explicit intervehicle communication.
We also show an application of this motion planner to a target trailing task, where a strategic planner commands USV waypoints based on high-level objectives, and the local motion planner ensures hazard avoidance and compliance with COLREGS during a traverse.
The COLREGS rules specify, for example, which vessel is responsible for giving way to the other and to which side of the “stand-on” vessel to maneuver. Three primary COLREGS rules are considered in this paper: crossing, overtaking, and head-on situations. For autonomous USVs to be safely deployed in environments with other traffic boats, it is imperative that the USV's navigation algorithm obeys COLREGS. Furthermore, when other boats disregard their responsibility under COLREGS, the USV must fall back to its HA algorithms to prevent a collision.
The proposed approach is based on velocity obstacles (VO) method, which generates a cone-shaped obstacle in the velocity space. Because VOs also specify on which side of the obstacle the vehicle will pass during the avoidance maneuver, COLREGS are encoded in the velocity space in a natural way. Results from several experiments involving up to four vessels are presented, in what we believe is the first on-water demonstration of autonomous COLREGS maneuvers without explicit intervehicle communication.
We also show an application of this motion planner to a target trailing task, where a strategic planner commands USV waypoints based on high-level objectives, and the local motion planner ensures hazard avoidance and compliance with COLREGS during a traverse.
Scheduling Cluster Tools with Ready Time Constraints for Consecutive Small Lots
In the semiconductor manufacturing industry, the lot size currently tends to be extremely small, even being only 5-8 wafers, whereas conventional lots have 25 identical wafers. The smaller lot size is made because customers demand extremely small lots, and the number of chips in a large 300 mm wafer has increased. Cyclic scheduling is not applicable for such small lot production because the number of identical work cycles accounts for a small proportion of scheduling as compared to the lengths of the starting and closing transient periods.
We therefore examine a new noncyclic scheduling problem of cluster tools for small lot production that considers ready time constraints on the chambers and the robot. The ready times are the epochs when the resources are freed from processing the preceding lot. To solve the scheduling problem, we develop a Petri net model which is a graphical and mathematical method for discrete event dynamic systems.
Based on the Petri net model, we also develop a mixed integer programming (MIP) model and a branch and bound (B&B) algorithm for determining an optimal schedule. The B&B algorithm solves lots with up to 25 wafers and eight wafers within 500 s for a single-armed cluster tool and a dual-armed cluster tool, respectively, when three process steps are considered.
Therefore, we propose an approximation method for the dual-armed cluster tool that schedules only the first few wafers with the B&B algorithm and the succeeding wafers with a well-known cyclic sequence. From experiments, we conclude that the difference between the approximation method and an optimal makespan is less than 1%. The methods we propose can be used for general noncyclic scheduling problems that can be modeled by Petri nets.
We therefore examine a new noncyclic scheduling problem of cluster tools for small lot production that considers ready time constraints on the chambers and the robot. The ready times are the epochs when the resources are freed from processing the preceding lot. To solve the scheduling problem, we develop a Petri net model which is a graphical and mathematical method for discrete event dynamic systems.
Based on the Petri net model, we also develop a mixed integer programming (MIP) model and a branch and bound (B&B) algorithm for determining an optimal schedule. The B&B algorithm solves lots with up to 25 wafers and eight wafers within 500 s for a single-armed cluster tool and a dual-armed cluster tool, respectively, when three process steps are considered.
Therefore, we propose an approximation method for the dual-armed cluster tool that schedules only the first few wafers with the B&B algorithm and the succeeding wafers with a well-known cyclic sequence. From experiments, we conclude that the difference between the approximation method and an optimal makespan is less than 1%. The methods we propose can be used for general noncyclic scheduling problems that can be modeled by Petri nets.
Security of Autonomous Systems Employing Embedded Computing and Sensors
Embedded computing and sensor systems are increasingly becoming an integral part of today's infrastructure. From jet engines to vending machines, our society relies on embedded computing and sensor systems to support numerous applications seamlessly and reliably.
This is especially true with respect to autonomous systems such as unmanned aircraft, unmanned ground vehicles, robotics, medical operations, and industrial automation. However, given society's increasing reliance on embedded computing and sensor systems as well as the applications they support, this introduces a new form of vulnerability into this critical infrastructure that is only now beginning to be recognized as a significant threat with potentially serious consequences.
This column presents the latest insights on the technical challenges and opportunities associated with the security of autonomous systems from an embedded computing and sensors perspective.
This is especially true with respect to autonomous systems such as unmanned aircraft, unmanned ground vehicles, robotics, medical operations, and industrial automation. However, given society's increasing reliance on embedded computing and sensor systems as well as the applications they support, this introduces a new form of vulnerability into this critical infrastructure that is only now beginning to be recognized as a significant threat with potentially serious consequences.
This column presents the latest insights on the technical challenges and opportunities associated with the security of autonomous systems from an embedded computing and sensors perspective.
Self-Configuration of Waypoints for Docking Maneuvers of Flexible Automated Guided Vehicles
We study the problem of automatic configuration of the initial position, the so-called waypoint, from which to initiate a robust and accurate docking maneuver using nonholonomic (car-like) robotic forklifts in the context of automated manufacturing.
The proper selection of these positions is of paramount importance to operate with the industrial grade of accuracy, repeatability, and reliability required by load transfer operations in industrial settings.
An unconstrained optimization method coupled with probabilistic techniques is proposed to solve this problem. The proposed method permits to increase significantly the flexibility and adaptability of the autonomous robotic forklifts.
The proper selection of these positions is of paramount importance to operate with the industrial grade of accuracy, repeatability, and reliability required by load transfer operations in industrial settings.
An unconstrained optimization method coupled with probabilistic techniques is proposed to solve this problem. The proposed method permits to increase significantly the flexibility and adaptability of the autonomous robotic forklifts.
Self-recognition of Vehicle Position Using UHF Passive RFID Tags
This paper proposes a method that enables self-recognition of a mobile vehicle's current position by utilizing ultrahigh frequency (UHF) passive radio-frequency identification (RFID) tags. The proposed method can be used in real industry environments such as complex storage warehouses where many different goods are dispersed throughout a wide area.
In particular, the proposed method makes use of two UHF RFID readers with identical emission configuration attached to a vehicle to identify a reference RFID tag. By utilizing the received signal strength indicator obtained by the readers from the reference RFID tag, the precise position of the moving vehicle can be obtained.
The experiments prove the effectiveness of the proposed method in accurately estimating the vehicle position.
In particular, the proposed method makes use of two UHF RFID readers with identical emission configuration attached to a vehicle to identify a reference RFID tag. By utilizing the received signal strength indicator obtained by the readers from the reference RFID tag, the precise position of the moving vehicle can be obtained.
The experiments prove the effectiveness of the proposed method in accurately estimating the vehicle position.
Sensor Network based Oil Well health monitoring and intelligent control
Most oil pumping units (OPUs) have been using manual control in the oilfield. This existing oil-pumping system, a high power-consuming process, has the incapability of OPU's structural health monitoring. In this paper, a sensor network based intelligent control is proposed for power economy and efficient oilwell health monitoring.
The proposed sensor network consists of three-level sensors: (1) several types of basic sensors, such as load sensor, angular sensor, voltage sensor, current sensor and oil pressure sensor, which are the first level sensors (FLS), are used for oilwell data sensing; (2) our developed intelligent sensors (IS), which belong to the second level sensor, are designed mainly for an oilwell's data elementary processing, main fault alarm/indication, typical data storage/indication, data/status transmission up to the third level sensor (TLS), data/status transmission between IS, and command transmission down to the OPU motor; and (3) our developed software-defined (SD) control centers with an embedded database, i.e., the TLS, are designed for hundreds of oilwells data storage/management, data processing, malfunction detection, malfunction alarm/indication, stroke-adjustment command transmission down to a specific IS for power economy and the malfunction report to the maintenance staff via global system for mobile communications (GSM) short message service (SMS). Experiment results at the Chinese Petroleum's Changqing Oilfield demonstrate our proposed sensor network based system.
The proposed sensor network consists of three-level sensors: (1) several types of basic sensors, such as load sensor, angular sensor, voltage sensor, current sensor and oil pressure sensor, which are the first level sensors (FLS), are used for oilwell data sensing; (2) our developed intelligent sensors (IS), which belong to the second level sensor, are designed mainly for an oilwell's data elementary processing, main fault alarm/indication, typical data storage/indication, data/status transmission up to the third level sensor (TLS), data/status transmission between IS, and command transmission down to the OPU motor; and (3) our developed software-defined (SD) control centers with an embedded database, i.e., the TLS, are designed for hundreds of oilwells data storage/management, data processing, malfunction detection, malfunction alarm/indication, stroke-adjustment command transmission down to a specific IS for power economy and the malfunction report to the maintenance staff via global system for mobile communications (GSM) short message service (SMS). Experiment results at the Chinese Petroleum's Changqing Oilfield demonstrate our proposed sensor network based system.
Sensorless Control of BLDC Motor Drive for an Automotive Fuel Pump using a Hysteresis Comparator
This paper develops the brushless dc (BLDC) motor sensorless control system for an automotive fuel pump. The sensorless techniques based on a hysteresis comparator and a potential start-up method with a high starting torque are suggested.
The hysteresis comparator is used to compensate for the phase delay of the back-EMFs due to a low-pass filter (LPF) and also prevent multiple output transitions from noise or ripple in the terminal voltages. The rotor position is aligned at standstill for maximum starting torque without an additional sensor and any information of motor parameters.
Also, the stator current can be easily adjusted by modulating the pulse width of the switching devices during alignment. Some experiments are implemented on a single chip DSP controller to demonstrate the feasibility of the suggested sensorless and start-up techniques.
The hysteresis comparator is used to compensate for the phase delay of the back-EMFs due to a low-pass filter (LPF) and also prevent multiple output transitions from noise or ripple in the terminal voltages. The rotor position is aligned at standstill for maximum starting torque without an additional sensor and any information of motor parameters.
Also, the stator current can be easily adjusted by modulating the pulse width of the switching devices during alignment. Some experiments are implemented on a single chip DSP controller to demonstrate the feasibility of the suggested sensorless and start-up techniques.
Shared Steering Control Between a Driver and an Automation: Stability in the Presence of Driver Behavior Uncertainty
This paper presents an advanced driver assistance system (ADAS) for lane keeping, together with an analysis of its performance and stability with respect to variations in driver behavior. The automotive ADAS proposed is designed to share control of the steering wheel with the driver in the best possible way. Its development was derived from an H2-Preview optimization control problem, which is based on a global driver–vehicle–road (DVR) system.
The DVR model makes use of a cybernetic driver model to take into account any driver–vehicle interactions. Such a formulation allows 1) considering driver assistance cooperation criteria in the control synthesis, 2) improving the performance of the assistance as a cooperative copilot, and 3) analyzing the stability of the whole system in the presence of driver model uncertainty. The results have been experimentally validated with one participant using a fixed-base driving simulator.
The developed assistance system improved lane-keeping performance and reduced the risk of a lane departure accident. Good results were obtained using several criteria for human–machine cooperation. Poor stability situations were successfully avoided due to the robustness of the whole system, in spite of a large range of driver model uncertainty.
The DVR model makes use of a cybernetic driver model to take into account any driver–vehicle interactions. Such a formulation allows 1) considering driver assistance cooperation criteria in the control synthesis, 2) improving the performance of the assistance as a cooperative copilot, and 3) analyzing the stability of the whole system in the presence of driver model uncertainty. The results have been experimentally validated with one participant using a fixed-base driving simulator.
The developed assistance system improved lane-keeping performance and reduced the risk of a lane departure accident. Good results were obtained using several criteria for human–machine cooperation. Poor stability situations were successfully avoided due to the robustness of the whole system, in spite of a large range of driver model uncertainty.
Simultaneous Fault Section Estimation and Protective Device Failure Detection using Percentage Values of the Protective Devices Alarms
This paper proposes a new approach to fault diagnosis in electrical power systems, which presents an aspect little explored in the literature that is the protective device failure detection together with the fault section estimation, since the majority of the methodologies so far proposed to fault diagnosis are limited to the fault section estimation alone.
The proposed methodology makes use of operation states of protective devices as well as information related to the protection philosophy. Initially, these data undergo a preprocessing step to convert the format of 0 and 1 to percentage values. The conversion to percentage values allows the use of artificial neural networks, whose numbers of inputs do not depend on the number of alarms of the protection philosophy, or the type of bus arrangement or the number of circuit breakers.
This allows the same set of neural networks to be trained and applied in different power systems with different protection schemes and bus arrangements. The proposed system has five neural networks, each containing few neurons and requiring 30 µs to perform fault diagnosis.
The proposed system was trained considering the IEEE 57-bus system, containing different selective protection schemes, and subsequently tested in the IEEE 14-bus, 30-bus, and 118-bus systems, and Eletronorte 230-kV real power system.
The proposed methodology makes use of operation states of protective devices as well as information related to the protection philosophy. Initially, these data undergo a preprocessing step to convert the format of 0 and 1 to percentage values. The conversion to percentage values allows the use of artificial neural networks, whose numbers of inputs do not depend on the number of alarms of the protection philosophy, or the type of bus arrangement or the number of circuit breakers.
This allows the same set of neural networks to be trained and applied in different power systems with different protection schemes and bus arrangements. The proposed system has five neural networks, each containing few neurons and requiring 30 µs to perform fault diagnosis.
The proposed system was trained considering the IEEE 57-bus system, containing different selective protection schemes, and subsequently tested in the IEEE 14-bus, 30-bus, and 118-bus systems, and Eletronorte 230-kV real power system.
Smart Personal Sensor Network Control for Energy Saving in a DC Grid Powered Led
Emerging smart grid technologies aim to renovate traditional power grid by integrating intelligent devices and their communications for monitoring and automation of the power grid to enable efficient demand-side energy management. In this paper, energy management in smart dc building grid powered dc electrical appliances like lighting is investigated, in particular energy savings from proposed personal lighting management strategy.
Unlike conventional fluorescent lamps powered mainly by ac grid, LED luminaires are dc in nature, thus results in significant power conversion losses, if operate on traditional ac powered system, are analyzed with proposed dc distribution building grid for LED lighting. This paper continues to explore the use of smart wireless sensors for personal control of the dc grid powered networked LED lighting.
Experimental results show that the proposed smart LED lighting system with an energy saving mechanism incorporated is able to achieve similar lighting performance as the conventional lighting condition, while at the same time, able to attain about 44% energy saving as compared to the original ac fluorescent system. For a low voltage dc grid being implemented, the maximum power loss and voltage drop of the developed dc distribution building grid are 2.25% and 3% respectively.
Unlike conventional fluorescent lamps powered mainly by ac grid, LED luminaires are dc in nature, thus results in significant power conversion losses, if operate on traditional ac powered system, are analyzed with proposed dc distribution building grid for LED lighting. This paper continues to explore the use of smart wireless sensors for personal control of the dc grid powered networked LED lighting.
Experimental results show that the proposed smart LED lighting system with an energy saving mechanism incorporated is able to achieve similar lighting performance as the conventional lighting condition, while at the same time, able to attain about 44% energy saving as compared to the original ac fluorescent system. For a low voltage dc grid being implemented, the maximum power loss and voltage drop of the developed dc distribution building grid are 2.25% and 3% respectively.
Smartphone Enabled Dangerous Driving Report System
This paper proposes a novel dangerous driving report system using a smart phone platform. By collecting a stream of data through built-in GPS receiver, a time series of speed profile can be obtained for a given journey.
An algorithm is proposed to detect anomaly in speed profile in order to detect whether a vehicle is speeding. As well as the ability to alert passengers in real-time in the case of speeding, the proposed system also records the journey data to be used as evidence when making a report.
This is a feature which is not yet possible in the traditional dangerous driving report deployed in Thailand. A case study using three different smart phones in the proposed framework is performed. The findings reveal that the data from Smart phone is as accurate as the values from car's speedometer with a speed offset of approximately 4km/hr.
An algorithm is proposed to detect anomaly in speed profile in order to detect whether a vehicle is speeding. As well as the ability to alert passengers in real-time in the case of speeding, the proposed system also records the journey data to be used as evidence when making a report.
This is a feature which is not yet possible in the traditional dangerous driving report deployed in Thailand. A case study using three different smart phones in the proposed framework is performed. The findings reveal that the data from Smart phone is as accurate as the values from car's speedometer with a speed offset of approximately 4km/hr.
Soft-core Processor Optimization According to Real-Application Requirements
Nowadays, embedded processor cores are integrated into most system-on-chip (SoC). Processor cores can be designed to be dedicated for an SoC. However, reusing of generic processors is often preferred due to time to market constraint.
Such processors have drawbacks in terms of hardware complexity and power consumption. Indeed, some of their instructions and hardware resources are useless. These area and energy inefficiencies are problematic for low-cost and low-energy systems. In this paper, we propose a methodology for automatically reducing processor functionalities and the resulting hardware complexity according to real-application requirements.
This approach was evaluated on two open-source processor cores. The results show that the average area and power consumption savings are over 20% on both application-specific integrated circuit (ASIC) and field-programmable gate array (FPGA) technologies.
Such processors have drawbacks in terms of hardware complexity and power consumption. Indeed, some of their instructions and hardware resources are useless. These area and energy inefficiencies are problematic for low-cost and low-energy systems. In this paper, we propose a methodology for automatically reducing processor functionalities and the resulting hardware complexity according to real-application requirements.
This approach was evaluated on two open-source processor cores. The results show that the average area and power consumption savings are over 20% on both application-specific integrated circuit (ASIC) and field-programmable gate array (FPGA) technologies.
Speed Control of Electrical Drives Using Classical Control Methods
A classical control approach to the design and analysis of proportional-integral (PI) speed controllers for electrical drives is presented. After vindicating the fact that traditional one-degree-of-freedom PI control generally gives unsatisfactory performance, a well-performing two-degree-of-freedom PI controller is designed, with analytical parameter selection.
The robustness of the obtained closed-loop system is analyzed and is found to be satisfactory. All the proposed control designs are validated by means of experiments.
The robustness of the obtained closed-loop system is analyzed and is found to be satisfactory. All the proposed control designs are validated by means of experiments.
Stochastic Approach for Short-Term Freeway Traffic Prediction during Peak Periods
Using a stochastic approach, this paper explores and models the basic stochastic characteristics of freeway traffic behavior under a wide range of traffic conditions during peak periods and then applies the models to short-term traffic speed prediction. The speed transition probabilities are estimated from real-world 30-s speed data over a six-year period at three different locations along the 38-mi corridor of Interstate 4 (I-4) in Orlando, FL.
The cumulative negative/positive transition probabilities and expected values are derived from the transition probabilities and fitted using logistic and exponential models, respectively. The expected values associated with the most likely transition of speed are then derived from the fitted models and used for predicting speed. Each predicted speed is also associated with a probability value, indicating the chance of observing the occurrence of such transition.
The prediction performance was compared for three methods using the root mean square errors (RMSEs). The weighted average method was very close to the higher probability method in most cases. For the two probabilistic methods, the performance was slightly better for the morning peak periods than the evening peak period or all data combined.
While the prediction performance of the probabilistic models was comparable with those of other methods found in the literature, the probabilistic approach based on the higher probability provides estimates of the associated probability with each prediction. This provides a measure of confidence in the predicted values before such information is disseminated to the public by traffic agencies.
The cumulative negative/positive transition probabilities and expected values are derived from the transition probabilities and fitted using logistic and exponential models, respectively. The expected values associated with the most likely transition of speed are then derived from the fitted models and used for predicting speed. Each predicted speed is also associated with a probability value, indicating the chance of observing the occurrence of such transition.
The prediction performance was compared for three methods using the root mean square errors (RMSEs). The weighted average method was very close to the higher probability method in most cases. For the two probabilistic methods, the performance was slightly better for the morning peak periods than the evening peak period or all data combined.
While the prediction performance of the probabilistic models was comparable with those of other methods found in the literature, the probabilistic approach based on the higher probability provides estimates of the associated probability with each prediction. This provides a measure of confidence in the predicted values before such information is disseminated to the public by traffic agencies.
Swarm Intelligence Approaches to Optimal Power Flow Problem with Distributed Generator Failures in Power Networks
Distributed generation becomes more and more important in modern power systems. However, the increasing use of distributed generators causes the concerns on the increasing system risk due to their likely failure or uncontrollable power outputs based on such renewable energy sources as wind and the sun.
This work for the first time formulates an optimal power flow problem by considering controllable and uncontrollable distributed generators in power networks. The problem for the cases of single and multiple generator failures is addressed as an example. The methods are presented to find its power output solution of controllable online generators via particle swarm optimization and group search optimizer for coping with the difficult scenarios in a power network.
The proposed methods are tested on an IEEE 14-bus system, and several population initialization strategies are investigated and compared for the algorithms. The simulation results confirm their effectiveness for optimal power management and effective control of a power network.
This work for the first time formulates an optimal power flow problem by considering controllable and uncontrollable distributed generators in power networks. The problem for the cases of single and multiple generator failures is addressed as an example. The methods are presented to find its power output solution of controllable online generators via particle swarm optimization and group search optimizer for coping with the difficult scenarios in a power network.
The proposed methods are tested on an IEEE 14-bus system, and several population initialization strategies are investigated and compared for the algorithms. The simulation results confirm their effectiveness for optimal power management and effective control of a power network.
Switched Ethernet-based Real-Time Networked Control System with Multiple-Client–Server Architecture
This paper experimentally verifies that a multiple-client-server architecture based on switched Ethernet can be used as a real-time communication standard for possible applications in factory automation, by observing the effects of packet delays, network congestion, and packet loss on the performance of a networked control system (NCS). The NCS experimental setup used in this research involves real-time feedback control of multiple plants connected to one or more controllers over the network.
A multiclient-multiserver (MC-MS) architecture on a local area network (LAN) was developed using user datagram protocol as the communication protocol. In the single-client-single-server (SC-SS) system, as the Ethernet link utilization increased over 82%, the average packet delays and steady-state error of a dc motor speed-control system increased by 2231% and 304%, respectively.
As the link utilization increased beyond the threshold, employing an additional server in the NCS reduced average packet delays and also overcame the negative effects of Ethernet's flow control mechanism. The MC-MS architecture is tested with artificially generated random packet loss.
The standard deviation of steady-state error (SSE) at 80% utilization with packet loss is found to be 70.2% less than SC-SS and 200% less than multiclient-single-server architecture. The MC-MS architecture remained stable till 70% of control or measurement packet loss.
A multiclient-multiserver (MC-MS) architecture on a local area network (LAN) was developed using user datagram protocol as the communication protocol. In the single-client-single-server (SC-SS) system, as the Ethernet link utilization increased over 82%, the average packet delays and steady-state error of a dc motor speed-control system increased by 2231% and 304%, respectively.
As the link utilization increased beyond the threshold, employing an additional server in the NCS reduced average packet delays and also overcame the negative effects of Ethernet's flow control mechanism. The MC-MS architecture is tested with artificially generated random packet loss.
The standard deviation of steady-state error (SSE) at 80% utilization with packet loss is found to be 70.2% less than SC-SS and 200% less than multiclient-single-server architecture. The MC-MS architecture remained stable till 70% of control or measurement packet loss.
System and Method for Passive Surveillance in Indoor Environments based on Principal Components of The Signal Strength Variation
Efficient wireless sensor nodes have significantly motivated the usage of wireless sensor networks for intrusion detection and surveillance. A passive wireless surveillance network has the ability to detect humans by analyzing only the variations of the signal strength with respect to distance and alignment between nodes.
When a human passes through an area covered by radio network, his/her body interferes with radio signals resulting in signal strength variations due to absorption, reflection and diffraction. In this paper, we analyze the signal strength variation induced by human presence, as a reliable method for passive surveillance.
The proposed method analyzes principal components from a covariance matrix composed of samples that present signal strength variations gathered from wireless nodes. By using smart wireless outlets and inter-outlets communication signals, the original environment is not visually modified, but a certain level of sensorial intelligence is introduced without additional sensors.
Principal component analysis enhances the detection accuracy level and improves the overall robustness of the surveillance method. Compared to conventional sensor networks, the use of smart wireless outlets and signal strength analysis preserves the transparency of the surveillance system and supports high level of sensorial intelligence, retaining low installation costs.
When a human passes through an area covered by radio network, his/her body interferes with radio signals resulting in signal strength variations due to absorption, reflection and diffraction. In this paper, we analyze the signal strength variation induced by human presence, as a reliable method for passive surveillance.
The proposed method analyzes principal components from a covariance matrix composed of samples that present signal strength variations gathered from wireless nodes. By using smart wireless outlets and inter-outlets communication signals, the original environment is not visually modified, but a certain level of sensorial intelligence is introduced without additional sensors.
Principal component analysis enhances the detection accuracy level and improves the overall robustness of the surveillance method. Compared to conventional sensor networks, the use of smart wireless outlets and signal strength analysis preserves the transparency of the surveillance system and supports high level of sensorial intelligence, retaining low installation costs.
Tank-Like Module-based Climbing Robot using Passive Compliant Joints
This paper proposes an underactuated modular climbing robot with flat dry elastomer adhesives. This robot is designed to achieve high speed, high payload, and dexterous motions that are typical drawbacks of previous climbing robots. Each module is designed as a tread-wheeled mechanism to simultaneously realize high speed and high adhesive force.
Two modules are connected by compliant joints, which induce a positive preload on the front wheels resulting in stable climbing and high payload capacity. Compliant joints also help the robot to perform various transitions. An active tail is adopted to regulate the preload of the second module. Force transfer equations are derived and stable operating conditions are verified.
The stiffness coefficients of the compliant joints and the active tail force are determined optimally to satisfy the constraints of stable operation. The prototype two-module robot achieves 6-cm/s speed and 500-g payload capacity on vertical surfaces. The abilities of flat surface locomotion, internal, external, and thin-wall transitions, and overcoming various sized obstacles are validated through experiment.
The principle of joint compliance can be adopted in other climbing robots to enhance their stability and transition capability.
Two modules are connected by compliant joints, which induce a positive preload on the front wheels resulting in stable climbing and high payload capacity. Compliant joints also help the robot to perform various transitions. An active tail is adopted to regulate the preload of the second module. Force transfer equations are derived and stable operating conditions are verified.
The stiffness coefficients of the compliant joints and the active tail force are determined optimally to satisfy the constraints of stable operation. The prototype two-module robot achieves 6-cm/s speed and 500-g payload capacity on vertical surfaces. The abilities of flat surface locomotion, internal, external, and thin-wall transitions, and overcoming various sized obstacles are validated through experiment.
The principle of joint compliance can be adopted in other climbing robots to enhance their stability and transition capability.
The House Intelligent Switch Control Network Based on CAN Bus
In this paper a building lighting intelligent switch control network is presented, which is based on CAN bus. According to the safety, stability and real time, the digital signals are used for the control unit, and the CAN bus is used as a communication of a distributed control network. A 16-bit MCU msp430f169 is used as the control unit, and the communication between the nodes is based on CAN bus.
This paper mainly introduces the design of the hardware and the software in detail. The experimental result shows this network system with high safety, stability and strong anti-jamming capability with practical significance and market value.
This paper mainly introduces the design of the hardware and the software in detail. The experimental result shows this network system with high safety, stability and strong anti-jamming capability with practical significance and market value.
The PLC based Control System for Intelligent Garage
For now, the urban land has become more scarce and expensive. So, for the parking lot, the traditional manual management mode that has low land utilization must be changed in order to decrease building area and enhance land utilization.
For this purpose, this paper proposes a design based on PLC to control intelligent garage. This plan uses the S7-300 serial products of Siemens as main control device, and use the HMI touch panel to collect the location information when picking or parking.
After being calculated by S7-300, a control signal will be transmitted to relay for moving the parking platform to assigned location, achieving that automation of car in and out garage management. The feasibility and validity of this system has been verified by software simulation in the STEP 7.
For this purpose, this paper proposes a design based on PLC to control intelligent garage. This plan uses the S7-300 serial products of Siemens as main control device, and use the HMI touch panel to collect the location information when picking or parking.
After being calculated by S7-300, a control signal will be transmitted to relay for moving the parking platform to assigned location, achieving that automation of car in and out garage management. The feasibility and validity of this system has been verified by software simulation in the STEP 7.
The Study for Application of ZIGBEE Location Tracing Monitoring System for ATM Device Theft
As the society has been computerized and automated, the crime for the ATM device is increased due to the wide distribution of ATM device, even the banking is easy. The theft is shown over 90%, the very high proportion among the Financial accident and crime.
With the locational characteristics of external ATM equipment that is always exposed to the crime, its accident even the theft to steal the ATM itself is not many, but it has been gradually every year.
With this social situation, the study is going to suggest the method to react rapidly and minimize the loss of damage by realizing the real time location, applying location tracing monitoring system using Zigbee as a rapid reaction to the theft for external ATM equipment.
With the locational characteristics of external ATM equipment that is always exposed to the crime, its accident even the theft to steal the ATM itself is not many, but it has been gradually every year.
With this social situation, the study is going to suggest the method to react rapidly and minimize the loss of damage by realizing the real time location, applying location tracing monitoring system using Zigbee as a rapid reaction to the theft for external ATM equipment.
The Wireless Transmission Design of a Novel Electronic Current Transformer
This study presents a novel electronic current transformer (ECT), which is based on the Hall current transformer (HCT), and a wireless transmission system. The novel ECT is aimed to be used in both measuring and protective current transformers, and the design of the wireless communication makes ECTs more flexible for current measurements at different current levels in power systems.
The novel ECT can be separated into three main circuits, including sensing signal processing circuit, analog-to-digital conversion circuit, and wireless circuit. Firstly, the scale of measured current is classified into small current, middle current, or large current. Then, analog to digital converter digitize the classified signal.
Finally, ZigBee device transmits the signal wirelessly to the data acquisition/monitoring system. If electric currents are detected as small or middle current levels, Irms and the reconstructing current proposed by this study will be sent to the monitoring system. Moreover, if electric current is detected as large/fault current level, an alarm will be sent immediately to monitoring system, and 10 cycles of the actual current will be sent later.
Besides, LabVIEW is used to build the data acquisition/monitoring system and the measurement result shows that the percentage current error between the transmitted signal from the ECT and the original signal is below 0.15%.
The novel ECT can be separated into three main circuits, including sensing signal processing circuit, analog-to-digital conversion circuit, and wireless circuit. Firstly, the scale of measured current is classified into small current, middle current, or large current. Then, analog to digital converter digitize the classified signal.
Finally, ZigBee device transmits the signal wirelessly to the data acquisition/monitoring system. If electric currents are detected as small or middle current levels, Irms and the reconstructing current proposed by this study will be sent to the monitoring system. Moreover, if electric current is detected as large/fault current level, an alarm will be sent immediately to monitoring system, and 10 cycles of the actual current will be sent later.
Besides, LabVIEW is used to build the data acquisition/monitoring system and the measurement result shows that the percentage current error between the transmitted signal from the ECT and the original signal is below 0.15%.
Thermal analysis and Characteristics Measurement System For Automotive health management for Based on RTOS
The battery management system (BMS) is an integral part of an automobile. It protects the battery from damage, predicts battery life, and maintains the battery in an operational condition. The BMS performs these tasks by integrating one or more of the functions, such as protecting the cell, thermal management, controlling the charge-discharge, determining the state of charge (SOC), state of health (SOH), and remaining useful life (RUL) of the battery, cell balancing, data acquisition, communication with on-board and off-board modules, as well as monitoring and storing historical data.
In this paper, we propose a BMS that estimates the critical characteristics of the battery (such as SOC, SOH, and RUL) using a data-driven approach. Our estimation procedure is based on a modified Randles circuit model consisting of resistors, a capacitor, the Warburg impedance for electrochemical impedance spectroscopy test data, and a lumped parameter model for hybrid pulse power characterization test data. The resistors in a Randles circuit model usually characterize the self-discharge and internal resistance of the battery, the capacitor generally represents the charge stored in the battery, and the Warburg impedance represents the diffusion phenomenon.
The Randles circuit parameters are estimated using a frequency-selective nonlinear least squares estimation technique, while the lumped parameter model parameters are estimated by the prediction error minimization method. We investigate the use of support vector machines (SVMs) to predict the capacity fade and power fade, which characterize the SOH of a battery, as well as estimate the SOC of the battery.
An alternate procedure for estimating the power fade and energy fade from low-current Hybrid Pulse Power characterization (L-HPPC) test data using the lumped parameter battery model has been proposed. Predictions of RUL of the battery are obtained by support vector regression of the power fade and capacity fade estimates.
Survival - - function estimates for reliability analysis of the battery are obtained using a hidden Markov model (HMM) trained using time-dependent estimates of capacity fade and power fade as observations. The proposed framework provides a systematic way for estimating relevant battery characteristics with a high-degree of accuracy.
In this paper, we propose a BMS that estimates the critical characteristics of the battery (such as SOC, SOH, and RUL) using a data-driven approach. Our estimation procedure is based on a modified Randles circuit model consisting of resistors, a capacitor, the Warburg impedance for electrochemical impedance spectroscopy test data, and a lumped parameter model for hybrid pulse power characterization test data. The resistors in a Randles circuit model usually characterize the self-discharge and internal resistance of the battery, the capacitor generally represents the charge stored in the battery, and the Warburg impedance represents the diffusion phenomenon.
The Randles circuit parameters are estimated using a frequency-selective nonlinear least squares estimation technique, while the lumped parameter model parameters are estimated by the prediction error minimization method. We investigate the use of support vector machines (SVMs) to predict the capacity fade and power fade, which characterize the SOH of a battery, as well as estimate the SOC of the battery.
An alternate procedure for estimating the power fade and energy fade from low-current Hybrid Pulse Power characterization (L-HPPC) test data using the lumped parameter battery model has been proposed. Predictions of RUL of the battery are obtained by support vector regression of the power fade and capacity fade estimates.
Survival - - function estimates for reliability analysis of the battery are obtained using a hidden Markov model (HMM) trained using time-dependent estimates of capacity fade and power fade as observations. The proposed framework provides a systematic way for estimating relevant battery characteristics with a high-degree of accuracy.
Thermoelectric Energy Harvesting of Human Body Heat for Wearable Sensors
The study of thermoelectric energy harvesting on people presented in this paper shows that although power generation is affected by many factors such as ambient temperature, wind speed, clothing thermal insulation, and a person's activity, it does not directly depend on metabolic rate as shown in the experiment.
The relevant thermal properties of humans measured at different ambient conditions are reported. Several thermopiles are either attached with a strap directly to the skin or integrated into garments in different locations on human body, and power generation is extensively studied at different ambient conditions. Textile covering thermopiles is found not to essentially decrease power generation.
Therefore, a hidden energy harvester is integrated into an office-style shirt and tested on people in real life. It generated power in 5-0.5 mW range at ambient temperatures of 15°C-27 °C, respectively. The thermoelectric shirt with such an energy harvester produces more energy during nine months of use (if worn 10 h/day) than the energy stored in alkaline batteries of the same thickness and weight.
The relevant thermal properties of humans measured at different ambient conditions are reported. Several thermopiles are either attached with a strap directly to the skin or integrated into garments in different locations on human body, and power generation is extensively studied at different ambient conditions. Textile covering thermopiles is found not to essentially decrease power generation.
Therefore, a hidden energy harvester is integrated into an office-style shirt and tested on people in real life. It generated power in 5-0.5 mW range at ambient temperatures of 15°C-27 °C, respectively. The thermoelectric shirt with such an energy harvester produces more energy during nine months of use (if worn 10 h/day) than the energy stored in alkaline batteries of the same thickness and weight.
Tour Planning for Mobile Data-Gathering Mechanisms in Wireless Sensor Networks
In this paper, we propose a new data-gathering mechanism for large-scale wireless sensor networks by introducing mobility into the network. A mobile data collector, for convenience called an M-collector in this paper, could be a mobile robot or a vehicle equipped with a powerful transceiver and battery, working like a mobile base station and gathering data while moving through the field.
An M-collector starts the data-gathering tour periodically from the static data sink, polls each sensor while traversing its transmission range, then directly collects data from the sensor in single-hop communications, and finally transports the data to the static sink. Since data packets are directly gathered without relays and collisions, the lifetime of sensors is expected to be prolonged. In this paper, we mainly focus on the problem of minimizing the length of each data-gathering tour and refer to this as the single-hop data-gathering problem (SHDGP).
We first formalize the SHDGP into a mixed-integer program and then present a heuristic tour-planning algorithm for the case where a single M-collector is employed. For the applications with strict distance/time constraints, we consider utilizing multiple M-collectors and propose a data-gathering algorithm where multiple M-collectors traverse through several shorter subtours concurrently to satisfy the distance/time constraints.
Our single-hop mobile data-gathering scheme can improve the scalability and balance the energy consumption among sensors. It can be used in both connected and disconnected networks. Simulation results demonstrate that the proposed data-gathering algorithm can greatly shorten the moving distance of the collectors compared with the covering line approximation algorithm and is close to the optimal algorithm for small networks.
In addition, the proposed data-gathering scheme can significantly prolong the network lifetime compared with a network with static data sink or a network in which the mobile collector c- n only move along straight lines.
An M-collector starts the data-gathering tour periodically from the static data sink, polls each sensor while traversing its transmission range, then directly collects data from the sensor in single-hop communications, and finally transports the data to the static sink. Since data packets are directly gathered without relays and collisions, the lifetime of sensors is expected to be prolonged. In this paper, we mainly focus on the problem of minimizing the length of each data-gathering tour and refer to this as the single-hop data-gathering problem (SHDGP).
We first formalize the SHDGP into a mixed-integer program and then present a heuristic tour-planning algorithm for the case where a single M-collector is employed. For the applications with strict distance/time constraints, we consider utilizing multiple M-collectors and propose a data-gathering algorithm where multiple M-collectors traverse through several shorter subtours concurrently to satisfy the distance/time constraints.
Our single-hop mobile data-gathering scheme can improve the scalability and balance the energy consumption among sensors. It can be used in both connected and disconnected networks. Simulation results demonstrate that the proposed data-gathering algorithm can greatly shorten the moving distance of the collectors compared with the covering line approximation algorithm and is close to the optimal algorithm for small networks.
In addition, the proposed data-gathering scheme can significantly prolong the network lifetime compared with a network with static data sink or a network in which the mobile collector c- n only move along straight lines.
Towards a New Modality-Independent Interface for a Robotic Wheelchair
This work presents the development of a robotic wheelchair that can be commanded by users in a supervised way or by a fully automatic unsupervised navigation system. It provides flexibility to choose different modalities to command the wheelchair, in addition to be suitable for people with different levels of disabilities. Users can command the wheelchair based on their eye blinks, eye movements, head movements, by sip-andpuff and through brain signals.
The wheelchair can also operate like an auto-guided vehicle, following metallic tapes, or in an autonomous way. The system is provided with an easy to use and flexible graphical user interface onboard a personal digital assistant, which is used to allow users to choose commands to be sent to the robotic wheelchair.
Several experiments were carried out with people with disabilities, and the results validate the developed system as an assistive tool for people with distinct levels of disability.
The wheelchair can also operate like an auto-guided vehicle, following metallic tapes, or in an autonomous way. The system is provided with an easy to use and flexible graphical user interface onboard a personal digital assistant, which is used to allow users to choose commands to be sent to the robotic wheelchair.
Several experiments were carried out with people with disabilities, and the results validate the developed system as an assistive tool for people with distinct levels of disability.
Towards a system for body-area sensing and detection of alcohol craving and mood dysregulation
Current methods in clinical psychology primarily rely on questionnaires and interviews with examiners. This paper presents preliminary work towards a smartphone-based wireless body area sensing system that will be used to improve current methods and provide real-time interventions if necessary.
This system consists of several wearable sensors for measuring physiological data, a smartphone, and a web server. The smartphone is the centerpiece, responsible for collecting sensor data, interacting with the user, performing real-time computation, and communicating with the web server.
The system collects physiological data, self-reported emotional and behavioral state, and other user-context data such as GPS location or ambient audio recording.
This system consists of several wearable sensors for measuring physiological data, a smartphone, and a web server. The smartphone is the centerpiece, responsible for collecting sensor data, interacting with the user, performing real-time computation, and communicating with the web server.
The system collects physiological data, self-reported emotional and behavioral state, and other user-context data such as GPS location or ambient audio recording.
Traffic Signal Control System Based on Wireless Technology
According to the requirements of traffic signal control, a new wireless traffic signal control system is developed in this paper. On the existing several kinds of wireless communication are compared and choose the most of them determine the most suitable for application in traffic controller technology in them.
In the design of network nodes, CC2530 wireless MCU was used as a kernel part of the network node in hardware design, the application program based on Z-Stack protocols.
In the design of network nodes, CC2530 wireless MCU was used as a kernel part of the network node in hardware design, the application program based on Z-Stack protocols.
Traffic Violation Detection Using Multiple Trajectories Evaluation of Vehicles
In general, lane change violations are likely to happen before the stop line in the red-light violation detection region. The system which can be detecting red-light and lane-change violation is very useful for the traffic management.
This paper present a novel method for the red-light violation detection using vehicles moving in the region of interest and combining with the evaluation of the trajectories behavior of multiple vehicles using mean square displacement (MSD) to detected both of violation.
We are using image processing technique only to detected traffic signal without help of another other system. The experiment result shows that the algorithm is high accuracy to detect both of violation.
This paper present a novel method for the red-light violation detection using vehicles moving in the region of interest and combining with the evaluation of the trajectories behavior of multiple vehicles using mean square displacement (MSD) to detected both of violation.
We are using image processing technique only to detected traffic signal without help of another other system. The experiment result shows that the algorithm is high accuracy to detect both of violation.
Triaxial Accelerometer-Based Fall Detection Method Using a Self-Constructing Cascade-AdaBoost-SVM Classifier
In this paper, we propose a cascade-AdaBoost-support vector machine (SVM) classifier to complete the triaxial accelerometer-based fall detection method. The method uses the acceleration signals of daily activities of volunteers from a database and calculates feature values.
By taking the feature values of a sliding window as an input vector, the cascade-AdaBoost-SVM algorithm can self-construct based on training vectors, and the AdaBoost algorithm of each layer can automatically select several optimal weak classifiers to form a strong classifier, which accelerates effectively the processing speed in the testing phase, requiring only selected features rather than all features.
In addition, the algorithm can automatically determine whether to replace the AdaBoost classifier by support vector machine. We used the UCI database for the experiment, in which the triaxial accelerometers are, respectively, worn around the left and right ankles, and on the chest as well as the waist. The results are compared to those of the neural network, support vector machine, and the cascade-AdaBoost classifier.
The experimental results show that the triaxial accelerometers around the chest and waist produce optimal results, and our proposed method has the highest accuracy rate and detection rate as well as the lowest false alarm rate.
By taking the feature values of a sliding window as an input vector, the cascade-AdaBoost-SVM algorithm can self-construct based on training vectors, and the AdaBoost algorithm of each layer can automatically select several optimal weak classifiers to form a strong classifier, which accelerates effectively the processing speed in the testing phase, requiring only selected features rather than all features.
In addition, the algorithm can automatically determine whether to replace the AdaBoost classifier by support vector machine. We used the UCI database for the experiment, in which the triaxial accelerometers are, respectively, worn around the left and right ankles, and on the chest as well as the waist. The results are compared to those of the neural network, support vector machine, and the cascade-AdaBoost classifier.
The experimental results show that the triaxial accelerometers around the chest and waist produce optimal results, and our proposed method has the highest accuracy rate and detection rate as well as the lowest false alarm rate.
Ultrasonic spectacles and waist belt for virtually impaired and blind person
This paper presents an electronic navigation system for visually impaired and blind people (subject). This system understands obstacles around the subject up to 500 cm in front, left and right direction using a network of ultrasonic sensors.
It effectively calculates distance of the detected object from the subject and prepares navigation path accordingly avoiding obstacles. It uses speech feedback to aware the subject about the detected obstacle and its distance.
This proposed system uses AT89S52 microcontroller based embedded system to process real time data collected using ultrasonic sensor network. Based on direction and distance of detected obstacle, relevant pre-recorded speech message stored in APR9600 flash memory is invoked. Such speech messages are conveyed to the subject using earphone.
It effectively calculates distance of the detected object from the subject and prepares navigation path accordingly avoiding obstacles. It uses speech feedback to aware the subject about the detected obstacle and its distance.
This proposed system uses AT89S52 microcontroller based embedded system to process real time data collected using ultrasonic sensor network. Based on direction and distance of detected obstacle, relevant pre-recorded speech message stored in APR9600 flash memory is invoked. Such speech messages are conveyed to the subject using earphone.
Uncertainty-Aware Household Appliance Scheduling Considering Dynamic Electricity Pricing in Smart Home
High quality demand side management has become indispensable in the smart grid infrastructure for enhanced energy reduction and system control. In this paper, a new demand side management technique, namely, a new energy efficient scheduling algorithm, is proposed to arrange the household appliances for operation such that the monetary expense of a customer is minimized based on the time-varying pricing model.
The proposed algorithm takes into account the uncertainties in household appliance operation time and intermittent renewable generation. Moreover, it considers the variable frequency drive and capacity-limited energy storage. Our technique first uses the linear programming to efficiently compute a deterministic scheduling solution without considering uncertainties.
To handle the uncertainties in household appliance operation time and energy consumption, a stochastic scheduling technique, which involves an energy consumption adaptation variable , is used to model the stochastic energy consumption patterns for various household appliances. To handle the intermittent behavior of the energy generated from the renewable resources, the offline static operation schedule is adapted to the runtime dynamic scheduling considering variations in renewable energy.
The simulation results demonstrate the effectiveness of our approach. Compared to a traditional scheduling scheme which models typical household appliance operations in the traditional home scenario, the proposed deterministic linear programming based scheduling scheme achieves up to 45% monetary expense reduction, and the proposed stochastic design scheme achieves up to 41% monetary expense reduction.
Compared to a worst case design where an appliance is assumed to consume the maximum amount of energy, the proposed stochastic design which considers the stochastic energy consumption patterns achieves up to 24% monetary expense reduction without violating the target trip rate of 0.5%. Furthermore, the proposed ener- y consumption scheduling algorithm can always generate the scheduling solution within 10 seconds, which is fast enough for household appliance applications.
The proposed algorithm takes into account the uncertainties in household appliance operation time and intermittent renewable generation. Moreover, it considers the variable frequency drive and capacity-limited energy storage. Our technique first uses the linear programming to efficiently compute a deterministic scheduling solution without considering uncertainties.
To handle the uncertainties in household appliance operation time and energy consumption, a stochastic scheduling technique, which involves an energy consumption adaptation variable , is used to model the stochastic energy consumption patterns for various household appliances. To handle the intermittent behavior of the energy generated from the renewable resources, the offline static operation schedule is adapted to the runtime dynamic scheduling considering variations in renewable energy.
The simulation results demonstrate the effectiveness of our approach. Compared to a traditional scheduling scheme which models typical household appliance operations in the traditional home scenario, the proposed deterministic linear programming based scheduling scheme achieves up to 45% monetary expense reduction, and the proposed stochastic design scheme achieves up to 41% monetary expense reduction.
Compared to a worst case design where an appliance is assumed to consume the maximum amount of energy, the proposed stochastic design which considers the stochastic energy consumption patterns achieves up to 24% monetary expense reduction without violating the target trip rate of 0.5%. Furthermore, the proposed ener- y consumption scheduling algorithm can always generate the scheduling solution within 10 seconds, which is fast enough for household appliance applications.
Using Multi-Robot Systems for Engineering Education: Teaching and Outreach with Large Numbers of an Advanced, Low-Cost Robot
This paper describes the experiences of using an advanced, low-cost robot in science, technology, engineering, and mathematics (STEM) education. It presents three innovations: It is a powerful, cheap, robust, and small advanced personal robot; it forms the foundation of a problem-based learning curriculum; and it enables a novel multi-robot curriculum while fostering collaborative team work on assignments.
The robot design has many features specific to educators: It is advanced enough for academic research, has a broad feature set to support a wide range of curricula, and is inexpensive enough to be an effective outreach tool. The low cost allows each student to have their own robot for the semester, so they can work on activities outside the classroom. This robot was used in three different classes in which it was the foundation for an innovative problem-based learning curriculum.
In particular, the robot has specialized sensors and a communications system that supports novel multi-robot curricula, which encourage student interaction in new ways. The results are promising; the robot was a big success in graduate, undergraduate, and outreach activities. Finally, student assessments indicate a greater interest and understanding of engineering and other STEM majors, and class evaluations were consistently above average
The robot design has many features specific to educators: It is advanced enough for academic research, has a broad feature set to support a wide range of curricula, and is inexpensive enough to be an effective outreach tool. The low cost allows each student to have their own robot for the semester, so they can work on activities outside the classroom. This robot was used in three different classes in which it was the foundation for an innovative problem-based learning curriculum.
In particular, the robot has specialized sensors and a communications system that supports novel multi-robot curricula, which encourage student interaction in new ways. The results are promising; the robot was a big success in graduate, undergraduate, and outreach activities. Finally, student assessments indicate a greater interest and understanding of engineering and other STEM majors, and class evaluations were consistently above average
Vehicle Positioning Using GSM and Cascade-Connected ANN Structures
Procuring location information for intelligent transportation systems is a popular topic among researchers. This paper investigates the vehicle location algorithm based on the received signal strength (RSS) from available Global System for Mobile Communications (GSM) networks.
The performances of positioning models, which consisted of cascade-connected (C-C) artificial neural network (ANN) multilayer feedforward structures employing the space-partitioning principle, are compared with the single-ANN multilayer feedforward model in terms of accuracy, the number of subspaces, and other positioning relevant parameters. C-C ANN structures make use of the fact that a vehicle can be found only in a subspace of the entire environment (roads) to improve the positioning accuracy.
The best-performing C-C ANN structure achieved an average error of 26 m and a median error of less than 5 m, which is accurate enough for most of the vehicle location services. Using the same RSS database obtained by measurements, it was shown that the proposed model outperforms kNN and extended Kalman filter (EKF)-trained ANN positioning algorithms. Moreover, the presented ANN structures replace not only the positioning algorithms but the overloaded map-matching process as well.
The performances of positioning models, which consisted of cascade-connected (C-C) artificial neural network (ANN) multilayer feedforward structures employing the space-partitioning principle, are compared with the single-ANN multilayer feedforward model in terms of accuracy, the number of subspaces, and other positioning relevant parameters. C-C ANN structures make use of the fact that a vehicle can be found only in a subspace of the entire environment (roads) to improve the positioning accuracy.
The best-performing C-C ANN structure achieved an average error of 26 m and a median error of less than 5 m, which is accurate enough for most of the vehicle location services. Using the same RSS database obtained by measurements, it was shown that the proposed model outperforms kNN and extended Kalman filter (EKF)-trained ANN positioning algorithms. Moreover, the presented ANN structures replace not only the positioning algorithms but the overloaded map-matching process as well.
Vehicular Traffic Density State Estimation Using Support Vector Machine
Road traffic congestion is a severe problem worldwide due to increased motorization, urbanization and population growth. Traffic congestion reduces the efficiency of the transportation infrastructure of a city; increases travel time, fuel consumption and air pollution, and leads to increased user frustration and fatigue.
Reducing traffic congestion can improve traffic flow, reduce travel times and the environmental impact. The main objective of this paper is to consider the problem of vehicular traffic density to determine the low and high traffic conditions. To determine the traffic firstly we determine the texture features. Based on the texture features we determine the various traffic conditions.
The procedure includes background subtraction from which we obtain the difference image and we apply the Support Vector Machine (SVM) procedure on a given captured image. Experimental result shows that the approaches are very efficient and produce up to 90% accuracy.
Reducing traffic congestion can improve traffic flow, reduce travel times and the environmental impact. The main objective of this paper is to consider the problem of vehicular traffic density to determine the low and high traffic conditions. To determine the traffic firstly we determine the texture features. Based on the texture features we determine the various traffic conditions.
The procedure includes background subtraction from which we obtain the difference image and we apply the Support Vector Machine (SVM) procedure on a given captured image. Experimental result shows that the approaches are very efficient and produce up to 90% accuracy.
Vibrational Energy Harvesting from Human Gait
Driven by the necessity to provide energy to wearable computing devices, the conversion of human movement into useful electrical energy has become a topic of extensive study. This paper presents a framework of calculating the maximal energy conversion from a resonant vibrational harvester during human gait.
Acceleration measurements from both recreational and elite athletes are used to estimate power output for various gait speeds. Significant power density was found to occur at the harmonics of the gait cadence with the maximum power density occurring at twice the gait frequency.
Though relatively large output power can occur at the first and second harmonics of the gait cadence, the resulting generator displacements are too large for practical use. Constraining the generator displacement to a root-mean-square magnitude of 25 mm provides approximately 28 mW of power for a 30-g device at optimal generator tuning conditions. As expected, the maximum power output increases with increasing electromechanical coupling and decreases with increasing damping.
Acceleration measurements from both recreational and elite athletes are used to estimate power output for various gait speeds. Significant power density was found to occur at the harmonics of the gait cadence with the maximum power density occurring at twice the gait frequency.
Though relatively large output power can occur at the first and second harmonics of the gait cadence, the resulting generator displacements are too large for practical use. Constraining the generator displacement to a root-mean-square magnitude of 25 mm provides approximately 28 mW of power for a 30-g device at optimal generator tuning conditions. As expected, the maximum power output increases with increasing electromechanical coupling and decreases with increasing damping.
Video Surveillance System And Facility To Access Pc From Remote Areas Using Smart Phone
Video surveillance is a popular consumer application that is used for various purposes such as public safety, facilities surveillance, and traffic monitoring. In this paper IP camera are employed for surveillance, and which unlike analog Closed Circuit Television (CCTV) cameras, it can send and receive data via a network and the Internet.
This is incredibly convenient and easy-to-use application. Motion Detector is an amazing app that turns the phone into a surveillance device with motion detection. Using the IP camera, Motion Detector Pro has the ability to detect the slightest of movements happening in the phone's range of vision.
If, at all, there's an intruder, the application will immediately alert you with an email or text message and there is a new app for transferring image from mobile to pc and vice versa using this app it provide the facility to store data in system itself . Data transmission app also allow to update data which is automatically updated in the system.
This is incredibly convenient and easy-to-use application. Motion Detector is an amazing app that turns the phone into a surveillance device with motion detection. Using the IP camera, Motion Detector Pro has the ability to detect the slightest of movements happening in the phone's range of vision.
If, at all, there's an intruder, the application will immediately alert you with an email or text message and there is a new app for transferring image from mobile to pc and vice versa using this app it provide the facility to store data in system itself . Data transmission app also allow to update data which is automatically updated in the system.
Virtual Battery – A Battery Simulation Framework for Electric Vehicles
The battery is one of the most important components in electric vehicles. In this paper, a virtual battery model, which provides a framework of battery simulation for electric vehicles, is introduced. Using such a framework, we can model and simulate the performance of a battery during its usage, such as battery charge, discharge, and idle status, the impacts of internal and external temperature, the manufacturing quality on joints, the cell capacity and balance management, etc.
Such a framework can provide a quantitative tool for design and manufacturing engineers to predict the battery performance, investigate the impacts of manufacturing process, and obtain feedback for improvement in battery design, control, and manufacturing processes. Note to Practitioners-Automotive battery manufacturing has become more and more important due to the need of alternative energy source to gasoline powered engines.
Although substantial amount of attention has been paid to study both individual battery cells and the battery pack as a whole, a battery model which includes interactions of all its components (cells, joints, external inputs, etc.) is not available, and the impact of manufacturing quality on battery performance has not been investigated.
In this paper, a virtual battery simulation framework is developed to evaluate battery performance under different circumstances, involving the issues of cell capacity, temperature, driving profile, the joint (manufacturing) quality, etc. Such a framework can help battery design and manufacturing engineers to evaluate battery performance, investigate the impacts of manufacturing practices, and provide feedback for improvement.
Such a framework can provide a quantitative tool for design and manufacturing engineers to predict the battery performance, investigate the impacts of manufacturing process, and obtain feedback for improvement in battery design, control, and manufacturing processes. Note to Practitioners-Automotive battery manufacturing has become more and more important due to the need of alternative energy source to gasoline powered engines.
Although substantial amount of attention has been paid to study both individual battery cells and the battery pack as a whole, a battery model which includes interactions of all its components (cells, joints, external inputs, etc.) is not available, and the impact of manufacturing quality on battery performance has not been investigated.
In this paper, a virtual battery simulation framework is developed to evaluate battery performance under different circumstances, involving the issues of cell capacity, temperature, driving profile, the joint (manufacturing) quality, etc. Such a framework can help battery design and manufacturing engineers to evaluate battery performance, investigate the impacts of manufacturing practices, and provide feedback for improvement.
Virtual electric wheelchair controlled by electromyographic signals.
Assistive technology is dedicated to people who suffers from disabilities or pathologies that limit their daily life. It provides support in alternative communication, accessibility, mobility and cognitive domains. An example of this type of technology is the electric wheelchair that allows the person to move more freely and independently.
However, most models are operated with a joystick, limiting their use to those who can manipulate it. Electromyographic signals can be used as an alternative method for controlling the vehicle by people with severe motor disabilities. Virtual simulators are good tools for testing different types of control and teaching future users how to drive it before moving on to a real model.
This paper presents an electromyography system adapted for controlling a virtual electric wheelchair simulator by using facial muscles. The designed system was successfully tested by a volunteer in a pilot study, providing an alternative way for controlling a wheelchair by users who can't operate a joystick.
However, most models are operated with a joystick, limiting their use to those who can manipulate it. Electromyographic signals can be used as an alternative method for controlling the vehicle by people with severe motor disabilities. Virtual simulators are good tools for testing different types of control and teaching future users how to drive it before moving on to a real model.
This paper presents an electromyography system adapted for controlling a virtual electric wheelchair simulator by using facial muscles. The designed system was successfully tested by a volunteer in a pilot study, providing an alternative way for controlling a wheelchair by users who can't operate a joystick.
Visual Control of an Automatic Manipulation System by Microscope and Pneumatic Actuator
This paper presents an automatic manipulation system consisting of microscope and pneumatic actuator. Through image captured by microscope with a CCD camera, the position between the probe and the object can be calculated in the image plane. A visual fuzzy controller is designed to improve the precision of a nonlinear pneumatic manipulator. From the experimental results, the position error of the system is below 1 pixel. The system can be applied to puncture fish embryo.
Water Environment Monitoring System Based on ZIGBEE Technology
Water environment monitoring system based on wireless sensor networks (WSNs) consists of three parts: data monitoring nodes, date video base station and remote monitoring center. For the sake of realizing to monitor large range waters such as reservoir, wetland, lake, river and ocean etc, the monitoring system has the function of perception, acquisition, processing and transmission for video-information in key areas and various water environment parameters, such as water temperature, PH, turbidity, electric conductivity, dissolved oxygen and so on.
As the gateway between those data monitoring nodes and CDMA network, the data video base station is communication center in the monitoring network. Based on ARM-DSP double processors architecture, the date video base station for water environment monitoring is studied and its software and hardware is designed in this paper.
Moreover, by means of ZigBee and CDMA wireless transmission technology, the base station realizes data bidirectional communication between the sensor networks and the remote monitoring center. It well meets the need of remote real time water environment monitoring system and also has wide application prospect in industrial control, smart home, medical telemetry and intelligent traffic, etc.
As the gateway between those data monitoring nodes and CDMA network, the data video base station is communication center in the monitoring network. Based on ARM-DSP double processors architecture, the date video base station for water environment monitoring is studied and its software and hardware is designed in this paper.
Moreover, by means of ZigBee and CDMA wireless transmission technology, the base station realizes data bidirectional communication between the sensor networks and the remote monitoring center. It well meets the need of remote real time water environment monitoring system and also has wide application prospect in industrial control, smart home, medical telemetry and intelligent traffic, etc.
Wearable Wireless Vital Monitoring Technology for Smart Health Care
Smart health care, that measures users' living conditions and health status using small sensing devices and collecting their data over a network under daily life, is expected as a new trend. It is getting paid more attention along with the increase of demands of preventive care.
In this paper, vital data rates and the amount of the data accumulation in a variety of smart health care use cases are discussed. Then, the relationship between the use cases and possible applications of short-range wireless systems is discussed.
Finally, our developed patch type wearable vital monitoring device that multiple numbers of vital sensors, a high performance processor and a dual mode Bluetooth transceiver are integrated into a 14.5×14.5mm module is introduced.
In this paper, vital data rates and the amount of the data accumulation in a variety of smart health care use cases are discussed. Then, the relationship between the use cases and possible applications of short-range wireless systems is discussed.
Finally, our developed patch type wearable vital monitoring device that multiple numbers of vital sensors, a high performance processor and a dual mode Bluetooth transceiver are integrated into a 14.5×14.5mm module is introduced.
Web based Remote Navigational Robot for Multiclass Human-Robot Interaction
Robots and human are inter-related because robots are built to serve human. Mobile robot that is equipped with vision capability and remote navigation is able to fulfill multiclass human-robot interaction (HRI) for various localization methods, interaction modes and human experience of the robot. With the advancement of embedded system and communication technology, robot can run on smaller platform and allow human navigation from distant location.
In this paper, design of a remote navigational mobile robot based on live video streaming and steering control via a web browser over the Wi-Fi network is presented. The robot acts as the server and the client is the remote human operator.
The project takes emphasis on building the robot that runs on a compact embedded system board, namely the Mini2440, for video streaming to remote client and linkage with the client to receive control inputs over the internet. The Mini2440 board also transfers the remote control inputs to a microcontroller board that runs on a PIC microcontroller through the UART interface. The microcontroller board then controls the pin electronics for the motor driver.
A self-contained mobile robot prototype for indoor navigation was built. Experiment result shows that live video streaming from server to client is achievable at average of 0.67s video lag through the MJPEG-streamer. Robot navigation has been performed with condition that the control tool used by the remote operator has sufficient processing power for online video feed.
In this paper, design of a remote navigational mobile robot based on live video streaming and steering control via a web browser over the Wi-Fi network is presented. The robot acts as the server and the client is the remote human operator.
The project takes emphasis on building the robot that runs on a compact embedded system board, namely the Mini2440, for video streaming to remote client and linkage with the client to receive control inputs over the internet. The Mini2440 board also transfers the remote control inputs to a microcontroller board that runs on a PIC microcontroller through the UART interface. The microcontroller board then controls the pin electronics for the motor driver.
A self-contained mobile robot prototype for indoor navigation was built. Experiment result shows that live video streaming from server to client is achievable at average of 0.67s video lag through the MJPEG-streamer. Robot navigation has been performed with condition that the control tool used by the remote operator has sufficient processing power for online video feed.
Wheelchair obstacle avoidance based on fuzzy Controller and ultrasonic sensors
Electric wheelchair is one of the most used for the movement of disabled and aged people. This work introduces an obstacle avoidance system aimed for providing more autonomous navigation of a electric wheelchair (EW) in unknown indoor environments.
These technologies seek to increase the independence of people with disabilities and improve their quality of life by making the most of each individuals abilities. Furthermore, the integration of an ultrasonic sensor to avoid obstacle and a fuzzy controller to generates velocity for aim to join the target position. A prototype of EW has been equipped with control unit based on two micro-controller.
The first for manage the motors velocity. The second for explore the ultrasonic sensors. Two micro-controller exchanges the information with a PC board type PC 104, which is used to process data from sensors and encoders. The information is processed by a control algorithm based on fuzzy logic.
The control algorithm is optimized using the gradient method to minimize the path traveled to reach the desired position. The practical implementation demonstrates the algorithm validity for obstacle avoidance and goal achievement with a minimum path and greater security.
These technologies seek to increase the independence of people with disabilities and improve their quality of life by making the most of each individuals abilities. Furthermore, the integration of an ultrasonic sensor to avoid obstacle and a fuzzy controller to generates velocity for aim to join the target position. A prototype of EW has been equipped with control unit based on two micro-controller.
The first for manage the motors velocity. The second for explore the ultrasonic sensors. Two micro-controller exchanges the information with a PC board type PC 104, which is used to process data from sensors and encoders. The information is processed by a control algorithm based on fuzzy logic.
The control algorithm is optimized using the gradient method to minimize the path traveled to reach the desired position. The practical implementation demonstrates the algorithm validity for obstacle avoidance and goal achievement with a minimum path and greater security.
Wireless and Piezoelectric Sensory Fusion System for Indoor Human/Robot Localization and Monitoring
An indoor localization and monitoring system for robots and people is an important issue in robotics research. Although several monitoring systems are currently under development by previous investigators, these issues remain significant difficulties. For instance, the pyroelectric IR (PIR) system provides less accurate information of human location and is restricted when there are multiple targets.
Furthermore, the RF localization system is constrained by its limited accuracy. In this study, we propose an indoor localization and monitoring system based on a wireless and PIR (WPIR) sensory fusion system. We develop a sensor-network-based localization method called the WPIR inference algorithm.
This algorithm determines the fused position from both the PIR localization system and RF signal localization system, which utilize the received signal strength propagation model. We have developed and experimentally demonstrated a WPIR sensory fusion system, which can be successfully applied in localizing multiple targets based on two robots and two people in this study. With an accurate localization mechanism for the indoor environment, the provision of appropriate services for people can be realized
Furthermore, the RF localization system is constrained by its limited accuracy. In this study, we propose an indoor localization and monitoring system based on a wireless and PIR (WPIR) sensory fusion system. We develop a sensor-network-based localization method called the WPIR inference algorithm.
This algorithm determines the fused position from both the PIR localization system and RF signal localization system, which utilize the received signal strength propagation model. We have developed and experimentally demonstrated a WPIR sensory fusion system, which can be successfully applied in localizing multiple targets based on two robots and two people in this study. With an accurate localization mechanism for the indoor environment, the provision of appropriate services for people can be realized
Wireless based load control and power monitoring system
Automations in industrial, commercial or residential sectors mostly depends upon the power systems, which requires distant controlling and monitoring. With the proliferation of wireless technologies, it is more efficient to implement an appropriate technology depending upon the cost, speed and distance requirements of the proposed system.
This paper provides a comparative study of different wireless protocols such as ZigBee (over IEEE 802.15.4) and Bluetooth (over IEEE 802.15.1) for the selection of appropriate technology for Load Control.
Further it describes a project model for remote controlling and monitoring of various loads/appliances and a means of efficient power utilization through real-time power consumption with the help of a PC-based GUI application.
This paper provides a comparative study of different wireless protocols such as ZigBee (over IEEE 802.15.4) and Bluetooth (over IEEE 802.15.1) for the selection of appropriate technology for Load Control.
Further it describes a project model for remote controlling and monitoring of various loads/appliances and a means of efficient power utilization through real-time power consumption with the help of a PC-based GUI application.
Wireless Black Box Using MEMS Accelerometer and GPS Tracking for Accidental Monitoring of Vehicles
In this work, wireless black box using MEMS accelerometer and GPS tracking system is developed for accidental monitoring. The system consists of cooperative components of an accelerometer, microcontroller unit, GPS device and GSM module.
In the event of accident, this wireless device will send mobile phone short massage indicating the position of vehicle by GPS system to family member, emergency medical service (EMS) and nearest hospital. The threshold algorithm and speed of motorcycle are used to determine fall or accident in real-time.
The system is compact and easy to install under rider seat. The system has been tested in real world applications using bicycles. The test results show that it can detect linear fall, non-linear fall and normal ride with high accuracy.
In the event of accident, this wireless device will send mobile phone short massage indicating the position of vehicle by GPS system to family member, emergency medical service (EMS) and nearest hospital. The threshold algorithm and speed of motorcycle are used to determine fall or accident in real-time.
The system is compact and easy to install under rider seat. The system has been tested in real world applications using bicycles. The test results show that it can detect linear fall, non-linear fall and normal ride with high accuracy.
Wireless Machine to Machine Healthcare Solution Using Android Mobile Devices in Global Networks
This paper presents a prototype machine-to-machine (M2M) healthcare solution that combines mobile and IPv6 techniques in a wireless sensor network to monitor the health condition of patients and provide a wide range of effective, comprehensive, and convenient healthcare services.
A low-power embedded wearable sensor measures the health parameters dynamically, and is connected, according to the concept of IPv6 over low-power wireless personal area network, to the M2M node for wireless transmission through the internet or external IP-enabled networks via the M2M gateway.
A visualization module of the server program graphically displays the recorded biomedical signals on Android mobile devices used by patients and doctors at the end of the networks in real-time. Our approach for a global M2M healthcare solution is managed to process the large amount of biomedical signals through the extended network combining IPv6 technique and mobile technology for daily lifestyle to users appropriately
A low-power embedded wearable sensor measures the health parameters dynamically, and is connected, according to the concept of IPv6 over low-power wireless personal area network, to the M2M node for wireless transmission through the internet or external IP-enabled networks via the M2M gateway.
A visualization module of the server program graphically displays the recorded biomedical signals on Android mobile devices used by patients and doctors at the end of the networks in real-time. Our approach for a global M2M healthcare solution is managed to process the large amount of biomedical signals through the extended network combining IPv6 technique and mobile technology for daily lifestyle to users appropriately
Wireless Sensor Network Based Home Monitoring System for Wellness Determination of Elderly
There are many issues in designing and implementing an intelligent wireless sensor network based smart home for monitoring the elderly. The smart home is based on a few smart and intelligent wireless sensors, which can be configured around a wireless ad-hoc network. The system will generate early warning message to care giver, when an unforeseen abnormal condition occurs. The costs and risks associated with system also dictate that unnecessary components be filtered from the system's design; therefore, all sensors in the network must justify their existence and purpose of the system.
An intelligent bed sensing system is very important to determine the quality of sleep of the inhabitant in the smart home. The paper has proposed an intelligent bed sensing system and trial results are presented
Wireless Sensor Network Based Smart Home: Sensor Selection, Deployment and Monitoring
The ubiquitous nature of miniature wireless sensors and rapid developments in the wireless network technology have revolutionized home monitoring and surveillance systems. The new means and methods of collecting data efficiently and have led to novel applications for indoor wireless sensor networks.
The applications are not limited to solely monitoring but can be extended to behavioral recognition. This can be of great value with the elderly as it can allow anomalous behavior to be detected and corrective actions taken accordingly. This paper details the installation and configuration of unobtrusive sensors in an elderly person's house - a smart home in the making - in a small city in New Zealand.
The overall system is envisaged to use machine learning to analyze the data generated by the sensor nodes. The novelty of this project is that instead of setting up an artificial test bed of sensors within the University premises, the sensors have been installed in a subject's home so that data can be collected in a real, not artificial, environment.
The applications are not limited to solely monitoring but can be extended to behavioral recognition. This can be of great value with the elderly as it can allow anomalous behavior to be detected and corrective actions taken accordingly. This paper details the installation and configuration of unobtrusive sensors in an elderly person's house - a smart home in the making - in a small city in New Zealand.
The overall system is envisaged to use machine learning to analyze the data generated by the sensor nodes. The novelty of this project is that instead of setting up an artificial test bed of sensors within the University premises, the sensors have been installed in a subject's home so that data can be collected in a real, not artificial, environment.
Wireless Sensor Network For Multi-Storey Building: Design and Implementation
In recent years, Wireless Sensor Network(WSN) is considered as a potential solution for home automation because of its reliability, low-cost, low-power consuming characteristics. Several researches have been carried out using WSN for home automation, however most studies have been experimented in small houses or in one storey of a building.
There has been little discussion about design and implementation of WSN automation system in multi-storey buildings. This paper describes a practical design and implementation of WSN for controlling and monitoring system in multi-storey building.
A building automation system using Micochip ZigBee WSN was developed and set up in the International University (IU) building for system evaluation. The performance results confirm that Micochip ZigBee WSN based home automation system is practically applicable in multi-storey building environment.
There has been little discussion about design and implementation of WSN automation system in multi-storey buildings. This paper describes a practical design and implementation of WSN for controlling and monitoring system in multi-storey building.
A building automation system using Micochip ZigBee WSN was developed and set up in the International University (IU) building for system evaluation. The performance results confirm that Micochip ZigBee WSN based home automation system is practically applicable in multi-storey building environment.
Wireless Surface Acoustic Wave Pressure and Temperature Sensor With Unique Identification Based on LiNbO3
Wireless sensor applications at elevated temperatures of around 200°C and above call for robust technologies such as surface acoustic wave (SAW) sensor designs. A combined pressure/temperature sensor with identification has been developed based on LiNbO3 substrate for condition monitoring applications in the baking industry.
Due to the given temperature specification and to avoid adhesives, the design of the sensor was conceived as a classical beam arrangement supported by three balls. This paper presents an overview on the design process of the sensor beginning with the mechanical simulation of the sensor and the derivation of the SAW delay line to measure pressure, temperature, and to realize an ID functionality.
The main result is a pressure sensitivity of 3.7 rad/bar with a temperature drift of 0.013 rad/°C. The sensitivity of the pressure sensor is also temperature dependent. This compound temperature drift can be compensated with the inherent temperature information of sensor.
Due to the given temperature specification and to avoid adhesives, the design of the sensor was conceived as a classical beam arrangement supported by three balls. This paper presents an overview on the design process of the sensor beginning with the mechanical simulation of the sensor and the derivation of the SAW delay line to measure pressure, temperature, and to realize an ID functionality.
The main result is a pressure sensitivity of 3.7 rad/bar with a temperature drift of 0.013 rad/°C. The sensitivity of the pressure sensor is also temperature dependent. This compound temperature drift can be compensated with the inherent temperature information of sensor.
Zigbee-assisted Power Saving Management for Mobile Devices
WiFi transmission can consume much energy on energy-constrained mobile devices. To improve energy efficiency, the Power Saving Management (PSM) has been standardized and applied.
The standard PSM, however, may not deliver satisfactory energy efficiency in many cases as the wakeup strategy adopted by it cannot adapt dynamically to traffic pattern changes. Motivated by the fact that it has been more and more popular for a mobile device to have both WiFi and other low-power wireless interfaces such as Bluetooth and ZigBee, we propose a ZigBee-assisted Power Saving Management (ZPSM) scheme, leveraging the ZigBee interface to wake up WiFi interface on demand to improve energy efficiency without violating delay requirements.
The simulation results have shown that ZPSM can save energy significantly without violating delay requirements in various scenarios
The standard PSM, however, may not deliver satisfactory energy efficiency in many cases as the wakeup strategy adopted by it cannot adapt dynamically to traffic pattern changes. Motivated by the fact that it has been more and more popular for a mobile device to have both WiFi and other low-power wireless interfaces such as Bluetooth and ZigBee, we propose a ZigBee-assisted Power Saving Management (ZPSM) scheme, leveraging the ZigBee interface to wake up WiFi interface on demand to improve energy efficiency without violating delay requirements.
The simulation results have shown that ZPSM can save energy significantly without violating delay requirements in various scenarios
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