Название: Human Activity Recognition and Behaviour Analysis: For Cyber-Physical Systems in Smart Environments Автор: Liming Chen, Chris D. Nugent
Издательство: Springer
Год: 2019
Страниц: 268
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
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 (AI) 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 (IoT). 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.
Recent advances in ubiquitous computing, sensing technologies, the Internet of Things, mobile computing and smart environments have led to a new wave of smart cyber-physical applications. These applications require human-machine systems to support context awareness, learning and cognitive capabilities, personalization and adaptation. Activity recognition and computational behaviour analysis are key to the success of such cyber-physical human-machine systems, as they provide essential contexts at multiple levels of abstraction for the aforementioned features.
Over years, there has been a constant shift of sensor observation modelling, representation, interpretation and usage, from low-level raw observation data and their direct/hardwired usage, data aggregation and fusion to high-level formal context modelling, activity recognition and behaviour analysis, and further to change detection, semantic interpretation, decision support and recommendation. It is envisioned that this trend will continue towards a further higher level of abstraction, achieving situation, activity and goal awareness to support smart cyber-physical human-machine systems in a wide range of applications such as smart homes, smart grid, intelligent transport, smart cities, to name but a few.
This book provides a systematic introduction on human activity recognition and behaviour analysis for cyber-physical human-machine systems in smart environments. It is built upon the authors’ extensive expertise, skills, experiences acquired over years’ research, as well as insights and visions on future research trends and directions.
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