Intelligent Sensor Networks: The Integration Of Sensor Networks, Signal Processing And Machine Learning,Used

Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning.Based on the worldclass research of awardwinning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, including compressive sensing and sampling, distributed signal processing, and intelligent signal learning. Presenting recent research results of worldrenowned sensing experts, the book is organized into three parts: Machine Learningdescribes the application of machine learning and other AI principles in sensor network intelligencecovering smart sensor/transducer architecture and data representation for intelligent sensors Signal Processingconsiders the optimization of sensor network performance based on digital signal processing techniquesincluding crosslayer integration of routing and applicationspecific signal processing as well as onboard image processing in wireless multimedia sensor networks for intelligent transportation systems Networkingfocuses on network protocol design in order to achieve an intelligent sensor networkingcovering energyefficient opportunistic routing protocols for sensor networking and multiagentdriven wireless sensor cooperationMaintaining a focus on 'intelligent' designs, the book details signal processing principles in sensor networks. It elaborates on critical platforms for intelligent sensor networks and illustrates key applicationsincluding target tracking, object identification, and structural health monitoring. It also includes a paradigm for validating the extent of spatiotemporal associations among data sources to enhance data cleaning in sensor networks, a sensor stream reduction application, and also considers the use of Kalman filters for attack detection in a water system sensor network that consists of water level sensors and velocity sensors.