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On multi-resident activity recognition in ambient smart-homes

  • Son N. TranEmail author
  • Dung Nguyen
  • Tung-Son Ngo
  • Xuan-Son Vu
  • Long Hoang
  • Qing Zhang
  • Mohan Karunanithi
Article
  • 26 Downloads

Abstract

Increasing attention to the research on activity monitoring in smart homes has motivated the employment of ambient intelligence to reduce the deployment cost and solve the privacy issue. Several approaches have been proposed for multi-resident activity recognition, however, there still lacks a comprehensive benchmark for future research and practical selection of models. In this paper, we study different methods for multi-resident activity recognition and evaluate them on the same sets of data. In particular, we explore the effectiveness and efficiency of temporal learning algorithms using sequential data and non-temporal learning algorithms using temporally-manipulated features. In the experiments we compare and analyse the results of the studied methods using datasets from three smart homes.

Keywords

Multiresident activity Pervasive computing Smart homes 

Notes

References

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.University of TasmaniaLauncestonAustralia
  2. 2.Duy Tan UniversityDa NangVietnam
  3. 3.Department of Computer ScienceFPT UniversityHanoiVietnam
  4. 4.Department of Computing ScienceUmeå UniversityUmeåSweden
  5. 5.Posts and Telecommunications Institute of TechnologyHo Chi Minh CityVietnam
  6. 6.The Australian E-Health Research CentreCSIROBrisbaneAustralia

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