Wireless localization techniques are an area that has attracted interest from both industry and academia, with self-localization capability providing a highly desirable characteristic of wireless sensor networks. Localization Algorithms and Strategies for Wireless Sensor Networks encompasses the significant and fast growing area of wireless localization techniques. This book provides comprehensive and up-to-date coverage of topics and fundamental theories underpinning measurement techniques and localization algorithms. A useful compilation for academicians, researchers, and practitioners, this Premier Reference Source contains relevant references and the latest studies emerging out of the wireless sensor network field.

The desire for precise knowledge about the location of a moving object at any time instant has motivated a great deal of scientific research recently. This is owing to a steady expansion of the range of enabling devices and technologies, as well as the need for seamless solutions for location-based services. Besides localization accuracy, a common requirement for emerging solutions is that they are cost-abstemious, both in terms of the financial and computational cost. Hence, development of localization strategies from already deployed technologies, e.g., from different terrestrial radio frequency sources is of great practical interest. Amongst other, these include localization strategies based on received signal strength (RSS), time of arrival, angle of arrival (AoA) or a combination of them. RSS-AoA-based Target Localization and Tracking in Wireless Sensor Networks presents recent advances in developing algorithms for target localization and tracking, reflecting the state-of-the-art algorithms and research achievements in target localization and tracking based on hybrid (RSS-AoA) measurements.Technical topics discussed in the book include:Centralized RSS-AoA-based Target LocalizationDistributed RSS-AoA-based Target LocalizationRSS-AoA-based Target Tracking via Maximum A Posteriori EstimatorRSS-AoA-based Target Tracking via Kalman FilterRSS-AoA-based via Sensor NavigationThis book is of interest for personnel in telecommunications and surveillance industries, military, smart systems, as well as academic staff and postgraduate/research students in telecommunications, signal processing, and non-smooth and convex optimization.

This book briefly summarizes the current state of the art technologies and solutions for location and tracking (L&T) in wireless sensor networks (WSN), focusing on RSS-based schemes. The authors offer broad and in-depth coverage of essential topics including range-based and range-free localization strategies, and signal path loss models. In addition, the book includes motion models and how state estimation techniques and advanced machine learning techniques can be utilized to design L&T systems for a given problem using low cost measurement metric (that is RSS). This book also provides MATLAB examples to demonstrate fundamental algorithms for L&T and provides online access to all MATLAB codes. The book allows practicing engineers and graduate students to keep pace with contemporary research and new technologies in the L&T domain.

This book gathers outstanding papers presented at the International Conference on Data Science and Applications (ICDSA 2021), organized by Soft Computing Research Society (SCRS) and Jadavpur University, Kolkata, India, from April 10 to 11, 2021. It covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative computing.

Mobile robots and Wireless Sensor Networks (WSNs) have enabled great potentials and a large space for ubiquitous and pervasive applications. Robotics and WSNs have mostly been considered as separate research fields and little work has investigated the marriage between these two technologies. However, these two technologies share several features, enable common cyber-physical applications and provide complementary support to each other. The primary objective of book is to provide a reference for cutting-edge studies and research trends pertaining to robotics and sensor networks, and in particular for the coupling between them. The book consists of five chapters. The first chapter presents a cooperation strategy for teams of multiple autonomous vehicles to solve the rendezvous problem. The second chapter is motivated by the need to improve existing solutions that deal with connectivity prediction, and proposed a genetic machine learning approach for link-quality prediction. The third chapter presents an architecture for indoor navigation using an Android smartphone for guiding a variety of users, from sighted to the visually impaired, to their intended destination. In chapter four, the authors deal with accurate prediction modeling of ocean currents for underwater glider navigation. In chapter five, the authors discuss the challenges and limitations of RSS-based localization mechanisms and propose, EasyLoc, an autonomous and practical RSS-based localization technique that satisfies ease of deployment and implementation.

Sensors were developed to detect and quantify structures and functions of human body as well as to gather information from the environment in order to optimize the efficiency, cost-effectiveness and quality of healthcare services as well as to improve health and quality of life. This book offers an up-to-date overview of the concepts, modeling, technical and technological details and practical applications of different types of sensors. It also discusses the trends for the next generation of sensors and systems for healthcare settings. It is aimed at researchers and graduate students in the field of healthcare technologies, as well as academics and industry professionals involved in developing sensing systems for human body structures and functions, and for monitoring activities and health.

The applications of positioning in wireless sensor networks include patient monitoring, asset tracking, and intelligent transportation including air traffic control. Popular methods are: received-signal-strength (RSS); time-of-arrival (TOA); time-difference-of-arrival (TDOA); and angle-of-arrival (AOA). Estimation is based on nonlinear equations constructed from measurements and knowledge of the anchor node geometry. In this thesis, anchor-based line-of-sight TOA and AOA are reviewed, and new techniques, namely DAOA (differential-angle-of-arrival) and hybrid TOA/DAOA are proposed for rotating laser implementation. For the TOA approach, a nonlinear Least Square Estimator (LSE) is applied to one- and two-dimensional systems, then the equations are linearized and solved by unconstrained/constrained LSE. This LSE procedure is also used for AOA. For DAOA, all the anchors are placed on a circle in order to simplify the solution, and then LSE is used to estimate an unlocalized node. The statistical accuracy of these methods, from simulation, is presented graphically for simple read-and-use application.