Activity Recognition in Pervasive Intelligent Environments

  • Liming Chen
  • Chris D. Nugent
  • Jit Biswas
  • Jesse Hoey

Part of the Atlantis Ambient and Pervasive Intelligence book series (ATLANTISAPI, volume 4)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Liming Chen, Ismail Khalil
    Pages 1-31
  3. Patrice C. Roy, Sylvain Giroux, Bruno Bouchard, Abdenour Bouzouane, Clifton Phua, Andrei Tolstikov et al.
    Pages 33-58
  4. Liang Wang, Tao Gu, Xianping Tao, Hanhua Chen, Jian Lu
    Pages 59-81
  5. Fulvio Mastrogiovanni, Antonello Scalmato, Antonio Sgorbissa, Renato Zaccaria
    Pages 83-109
  6. Diego López-de-Ipiña, Sergio Blanco, Xabier Laiseca, Ignacio Díaz-de-Sarralde
    Pages 111-125
  7. Shumei Zhang, Paul McCullagh, Chris Nugent, Huiru Zheng
    Pages 127-148
  8. Rachid Kadouche, Hélène Pigot, Bessam Abdulrazak, Sylvain Giroux
    Pages 149-164
  9. T. L. M. van Kasteren, G. Englebienne, B. J. A. Kröse
    Pages 165-186
  10. Norbert Noury, Julien Poujaud, Anthony Fleury, Ronald Nocua, Tareq Haddidi, Pierre Rumeau
    Pages 187-208
  11. Christoph Burghardt, Maik Wurdel, Sebastian Bader, Gernot Ruscher, Thomas Kirste
    Pages 209-236
  12. George Okeyo, Liming Chen, Hui Wang, Roy Sterritt
    Pages 237-263
  13. Clemens Lombriser, Oliver Amft, Piero Zappi, Luca Benini, Gerhard Tröster
    Pages 265-290
  14. Niket Shah, Maulik Kapuria, Kimberly Newman
    Pages 291-311
  15. Thomas Plötz, Paula Moynihan, Cuong Pham, Patrick Olivier
    Pages 313-329

About this book


This book consists of a number of chapters addressing different aspects of activity recognition, roughly in three main categories of topics. The first topic will be focused on activity modeling, representation and reasoning using mathematical models, knowledge representation formalisms and AI techniques. The second topic will concentrate on activity recognition methods and algorithms. Apart from traditional methods based on data mining and machine learning, we are particularly interested in novel approaches, such as the ontology-based approach, that facilitate data integration, sharing and automatic/automated processing. In the third topic we intend to cover novel architectures and frameworks for activity recognition, which are scalable and applicable to large scale distributed dynamic environments. In addition, this topic will also include the underpinning technological infrastructure, i.e. tools and APIs, that supports function/capability sharing and reuse, and rapid development and deployment of technological solutions. The fourth category of topic will be dedicated to representative applications of activity recognition in intelligent environments, which address the life cycle of activity recognition and their use for novel functions of the end-user systems with comprehensive implementation, prototyping and evaluation. This will include a wide range of application scenarios, such as smart homes, intelligent conference venues and cars.


activity recognition ambient intelligent datamining intelligent environments pervasive computing

Editors and affiliations

  • Liming Chen
    • 1
  • Chris D. Nugent
    • 2
  • Jit Biswas
    • 3
  • Jesse Hoey
    • 4
  1. 1., School of Computing and MathematicsUniversity of UlsterCounty AntrimUnited Kingdom
  2. 2.School of Computing & MathematicsUniversity of UlsterNewtownabbeyUnited Kingdom
  3. 3., Networking Protocols DepartmentInstitute of Infocomm ResearchSingaporeSingapore
  4. 4., School of Computer ScienceUniversity of WaterlooWaterlooCanada

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