[内容简介]
        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 Learningfocuses on the close integration of sensing, networking, and smart signal processing via machine learning.
        Based on the world-class research of award-winning 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 world-renowned sensing experts, the book is organized into three parts:
        
            - Machine Learning—describes the application of machine learning and other AI principles in sensor network intelligence—covering smart sensor/transducer architecture and data representation for intelligent sensors
 
            - Signal Processing—considers the optimization of sensor network performance based on digital signal processing techniques—including cross-layer integration of routing and application-specific signal processing as well as on-board image processing in wireless multimedia sensor networks for intelligent transportation systems
 
            - Networking—focuses on network protocol design in order to achieve an intelligent sensor networking—covering energy-efficient opportunistic routing protocols for sensor networking and multi-agent-driven wireless sensor cooperation
 
        
        Maintaining 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 applications—including 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.
        
        [目录]
        INTELLIGENT SENSOR NETWORKS: MACHINE LEARNING APPROACH
        Machine Learning Basics; Krasimira Kapitanova and Sang H. Son
        Modeling Unreliable Data and Sensors: Using Event Log Performance and F-Measure Attribute Selection; Vasanth Iyer, S. Sitharama Iyengar, and Srinivas Srivathsan
        Intelligent Sensor Interfaces and Data Format; Konstantin Mikhaylov, Joni Jamsa, Mika Luimula, Jouni Tervonen, and Ville Autio
        Smart Wireless Sensor Nodes for Structural Health Monitoring; Xuefeng Liu, Shaojie Tang, and Xiaohua Xu
        Knowledge Representation and Reasoning for the Design of Resilient Sensor Networks; David W. Kelle, Touria El-Mezyani, Sanjeev K. Srivastava, and David A. Cartes
        Intelligent Sensor-to-Mission Assignment; Hosam Rowaihy
        Prediction-Based Data Collection in Wireless Sensor Networks; Jann-Aël Le Borgne and Gianluca Bontempi
        Neuro-Disorder Patient Monitoring via Gait Sensor Networks: Toward an Intelligent, Context-Oriented Signal Processing; Fei Hu, Qingquan Sun, and Qi Hao
        Cognitive Wireless Sensor Networks; Sumit Kumar, Deepti Singhal, and Rama Murthy Garimella
        INTELLIGENT SENSOR NETWORKS: SIGNAL PROCESSING
        Routing for Signal Processing; Wanzhi Qiu and Efstratios Skafidas
        On-Board Image Processing in Wireless Multimedia Sensor Networks: A Parking Space Monitoring Solution for Intelligent Transportation Systems; Claudio Salvadori, Matteo Petracca, Marco Ghibaudi, and Paolo Pagano
        Signal Processing for Sensing and Monitoring Civil Infrastructure Systems; Mustafa Gul and F. Necati Catbas
        Data Cleaning in Low Powered Wireless Sensor Networks; Qutub Ali Bakhtiar, Niki Pissinou, and Kia Makki
        Sensor Stream Reduction; Andre L.L. Aquino, Paulo R.S. Silva Filho, Elizabeth F. Wanner, and Ricardo A. Rabelo
        Compressive Sensing and Its Application in Wireless Sensor Networks; Jae-Gun Choi, Sang-Jun Park, and Heung-No Lee
        Compressive Sensing for Wireless Sensor Networks; Mohammadreza Mahmudimanesh, Abdelmajid Khelil, and Neeraj Suri
        A Framework for Detecting Attacks on Sensors of Water Systems; Kebina Manandhar, Xiaojun Cao, and Fei Hu
        
        INTELLIGENT SENSOR NETWORKS: SENSORS AND SENSOR NETWORKS
        Reliable and Energy-Efficient Networking Protocol Design in Wireless Sensor Networks; Ting Zhu and Ping Yi
        Agent-Driven Wireless Sensors Cooperation for Limited Resources Allocation; Sameh Abdel-Naby, Conor Muldoon, Olga Zlydareva, and Gregory O’Hare
        Event Detection in Wireless Sensor Networks; Norman Dziengel, Georg Wittenburg, Stephan Adler, Zakaria Kasmi, Marco Ziegert, and Jochen Schiller
        Dynamic Coverage Problems in Sensor Networks; Hristo Djidjev and Miodrag Potkonjak
        Self-Organizing Distributed State Estimator; Joris Sijs and Zoltan Papp
        Low-Power Solutions for Wireless Passive Sensor Network Node Processor Architecture; Vyasa Sai, Ajay Ogirala, and Marlin H. Mickle
        Fusion of Pre/Post-RFID Correction Techniques to Reduce Anomalies; Peter Darcy, Prapassara Pupunwiwat, and Bela Stantic
        Radio Frequency Identification Systems and Sensor Integration for Telemedicine; Ajay Ogirala, Shruti Mantravadi, and Marlin H. Mickle
        Introduction: A New Generation of Intrusion Detection Networks; Jerry Krill, Michael O’Driscoll, and Natalie N. Dickins