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The book first defines the problems, various concepts and notions related to activity recognition, and introduces the fundamental rationale and state-of-the-art methodologies and approaches. It then describes the use of artificial intelligence techniques and advanced knowledge technologies for the modelling and lifecycle analysis of human activities and behaviours based on real-time sensing observations from sensor networks and the Internet of Things. It also covers inference and decision-support methods and mechanisms, as well as personalization and adaptation techniques, which are required for emerging smart human-machine pervasive systems, such as self-management and assistive technologies in smart healthcare. Each chapter includes theoretical background, technological underpinnings and practical implementation, and step-by-step information on how to address and solve specific problems in topical areas. This monograph can be used as a textbook for postgraduate and PhD students on courses such as computer systems, pervasive computing, data analytics and digital health. It is also a valuable research reference resource for postdoctoral candidates and academics in relevant research and application domains, such as data analytics, smart cities, smart energy, and smart healthcare, to name but a few. Moreover, it offers smart technology and application developers practical insights into the use of activity recognition and behaviour analysis in state-of-the-art cyber-physical systems. Lastly, it provides healthcare solution developers and providers with information about the opportunities and possible innovative solutions for personalized healthcare and stratified medicine.

Optical pattern recognition. --- Social sciences --- Computer Communication Networks. --- Big data. --- Data transmission systems. --- Pattern Recognition. --- Computer Appl. in Social and Behavioral Sciences. --- Information Systems Applications (incl. Internet). --- Big Data/Analytics. --- Input/Output and Data Communications. --- Data processing. --- Data communication systems --- Transmission of data --- Digital communications --- Electronic data processing --- Electronic systems --- Information theory --- Telecommunication systems --- Data sets, Large --- Large data sets --- Data sets --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Pattern recognition. --- Application software. --- Computer communication systems. --- Input-output equipment (Computers). --- Computer hardware --- Computer I/O equipment --- Computers --- Electronic analog computers --- Electronic digital computers --- Hardware, Computer --- I/O equipment (Computers) --- Input equipment (Computers) --- Input-output equipment (Computers) --- Output equipment (Computers) --- Computer systems --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Input-output equipment --- Distributed processing

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