Intelligent Wireless Binary Sensor Network System for Indoor Multiple Target Tracking - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Intelligent Wireless Binary Sensor Network System for Indoor Multiple Target Tracking write by Jiang Lu. This book was released on 2015. Intelligent Wireless Binary Sensor Network System for Indoor Multiple Target Tracking available in PDF, EPUB and Kindle. Multiple human tracking is desirable for many applications ranging from surveillance to gait biometrics, robotics and intelligent space. In recent, the low cost, low power consumption sensors, such as acoustic sensor, thermal sensors, pressure sensors, photonic sensors provide a new way to achieve multiple human tracking compared with the conventional tracking, such as Radar, Sonar and video tracking. Advances in sensor network technologies enable the development of distributed tracking systems. In this thesis, we attempt to explain the multiple human tracking problems with our binary pyroelectric infrared (PIR) sensors. We will cover from the designs of hardware sensor nodes to the problems of sensor node selection and calibration to the framework of binary compressive tracking to the implementation of distributed wireless senor system for tracking. In particular, we will investigate (a) A compressive multiple human tracking system using space encoding / decoding methods. (b) A Binary compressive tracking framework using low density parity check (LDPC) matrix and linear programming for encoding and decoding schemes. (c) A distributed information filter algorithm for tracking. (d) The information gain based sensor selection scheme and NMF based calibration scheme. The major accomplishments of this thesis include the following four aspects: (1) Space encoding and measurement decoding schemes. The space encoding scheme is based on the low density parity check (LDPC) matrix, which converts k-sparse target position vectors into different codewords. The measurement decoding scheme contains linear programming based localization and graphical model based tracking algorithms, which converts codewords into the states of multiple targets. A posterior Cram\'er-Rao bound analysis is utilized to achieve the tradeoff between the compression ratio of measurements and the accuracy of the tracking system. (2) Information driven sensors selection scheme. The information gain is used to dynamically adding sensors to maximize the information gain. The sensor selection procedure provides the maximum information gain for the whole sensor system which contains the minimum sensor numbers that can be used for tracking. (3) NMF based sensor calibration scheme. We provide a probability model for sensor calibration. Nonnegtive Matrix Factorization method is used to update the probability model. The calibration of sensor parameters, positions and orientations, then can be computed from the updated probability model. (4) Graphical model based problem illustration. We describe the graphical model for tracking algorithms. Various hidden variables can be added in graphical model. Also, a factor graph of tracking is provided to describe the distribute way of belief propagation.
Tracking Mobile Targets Through Wireless Sensor Networks
Tracking Mobile Targets Through Wireless Sensor Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Tracking Mobile Targets Through Wireless Sensor Networks write by Tareq Ali Alhmiedat. This book was released on 2009. Tracking Mobile Targets Through Wireless Sensor Networks available in PDF, EPUB and Kindle. In recent years, advances in signal processing have led to small, low power, inexpensive Wireless Sensor Network (WSN). The signal processing in WSN is different from the traditional wireless networks in two critical aspects: firstly, the signal processing in WSN is performed in a fully distributed manner, unlike in traditional wireless networks; secondly, due to the limited computation capabilities of sensor networks, it is essential to develop an energy and bandwidth efficient signal processing algorithms. Target localisation and tracking problems in WSNs have received considerable attention recently, driven by the necessity to achieve higher localisation accuracy, lower cost, and the smallest form factor. Received Signal Strength (RSS) based localisation techniques are at the forefront of tracking research applications. Since tracking algorithms have been attracting research and development attention recently, prolific literature and a wide range of proposed approaches regarding the topic have emerged. This thesis is devoted to discussing the existing WSN-based localisation and tracking approaches. This thesis includes five studies. The first study leads to the design and implementation of a triangulation-based localisation approach using RSS technique for indoor tracking applications. The presented work achieves low localisation error in complex environments by predicting the environmental characteristics among beacon nodes. The second study concentrates on investigating a fingerprinting localisation method for indoor tracking applications. The proposed approach offers reasonable localisation accuracy while requiring a short period of offline computation time. The third study focuses on designing and implementing a decentralised tracking approach for tracking multiple mobile targets with low resource requirements. Despite the interest in target tracking and localisation issues, there are few systems deployed using ZigBee network standard, and no tracking system has used the full features of the ZigBee network standard. Tracking through the ZigBee is a challenging task when the density of router and end-device nodes is low, due to the limited communication capabilities of end-device nodes. The fourth study focuses on developing and designing a practical ZigBee-based tracking approach. To save energy, different strategies were adopted. The fifth study outlines designing and implementing an energy-efficient approach for tracking applications. This study consists of two main approaches: a data aggregation approach, proposed and implemented in order to reduce the total number of messages transmitted over the network; and a prediction approach, deployed to increase the lifetime of the WSN. For evaluation purposes, two environmental models were used in this thesis: firstly, real experiments, in which the proposed approaches were implemented on real sensor nodes, to test the validity for the proposed approaches; secondly, simulation experiments, in which NS-2 was used to evaluate the power-consumption issues of the two approaches proposed in this thesis.
Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation
Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation write by Hu, Fei. This book was released on 2016-01-07. Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation available in PDF, EPUB and Kindle. The study of technology and its implications in the medical field has become an increasingly crucial area of research. By integrating technological innovations into clinical practices, patients can receive improved diagnoses and treatments, as well as faster and safer recoveries. Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation is an authoritative reference source for the latest scholarly research on the use of computer-assisted rehabilitation methods for disabled patients. Highlighting the application of robots, sensors, and virtual environments, this book is ideally designed for graduate students, engineers, technicians, and company administrators interested in the incorporation of auto-training methods in patient recovery.
Multi-target Tracking and Localization in Distributed Wireless Sensor Networks
Multi-target Tracking and Localization in Distributed Wireless Sensor Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multi-target Tracking and Localization in Distributed Wireless Sensor Networks write by Yinfei Fu. This book was released on 2010. Multi-target Tracking and Localization in Distributed Wireless Sensor Networks available in PDF, EPUB and Kindle.
Intelligent Wireless Sensor Networks and the Internet of Things
Intelligent Wireless Sensor Networks and the Internet of Things - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Intelligent Wireless Sensor Networks and the Internet of Things write by Bhanu Chander. This book was released on 2024-06-12. Intelligent Wireless Sensor Networks and the Internet of Things available in PDF, EPUB and Kindle. The edited book Intelligent Wireless Sensor Networks and Internet of Things: Algorithms, Methodologies and Applications is intended to discuss the progression of recent as well as future generation technologies for WSNs and IoTs applications through Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). In general, computing time is obviously increased when the massive data is required from sensor nodes in WSN’s. the novel technologies such as 5G and 6G provides enough bandwidth for large data transmissions, however, unbalanced links faces the novel constraints on the geographical topology of the sensor networks. Above and beyond, data transmission congestion and data queue still happen in the WSNs. This book: Addresses the complete functional framework workflow in WSN and IoT domains using AI, ML, and DL models Explores basic and high-level concepts of WSN security, and routing protocols, thus serving as a manual for those in the research field as the beginners to understand both basic and advanced aspects sensors, IoT with ML & DL applications in real-world related technology Based on the latest technologies such as 5G, 6G and covering the major challenges, issues, and advances of protocols, and applications in wireless system Explores intelligent route discovering, identification of research problems and its implications to the real world Explains concepts of IoT communication protocols, intelligent sensors, statistics and exploratory data analytics, computational intelligence, machine learning, and Deep learning algorithms for betterment of the smarter humanity Explores intelligent data processing, deep learning frameworks, and multi-agent systems in IoT-enabled WSN system This book demonstrates and discovers the objectives, goals, challenges, and related solutions in advanced AI, ML, and DL approaches This book is for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
