• DocumentCode
    1416726
  • Title

    Extracting and visualising human activity patterns of daily living in a smart home environment

  • Author

    Nam, Y. ; Rho, S. ; Lee, Sang-Rim

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Stony Brook Univ. - SUNY, Stony Brook, NY, USA
  • Volume
    5
  • Issue
    17
  • fYear
    2011
  • Firstpage
    2434
  • Lastpage
    2442
  • Abstract
    The authors present an approach that extracts human activity patterns of daily living and represents spatiotemporal relations between activities intuitively. In general, customised services are provided based on activity patterns of users. This study focuses on extracting and determining activities that occur simultaneously. In order to determine simultaneous activities, the authors analysed the daily activities that are collected from device applications such as location sensors and electronics. In addition, a context model using the incremental statistical method is organised and temporal relations between the activities patterns are analysed. Furthermore, information visualisation of the spatiotemporal topology with duration and frequency is demonstrated. Also, the authors have experimented on a test-bed called the ubiquitous smart space and compared the accuracy of the incremental statistical method with that of the non-incremental method.
  • Keywords
    biomedical measurement; data visualisation; feature extraction; health care; medical computing; statistical analysis; context model; daily living human activity patterns; human activity pattern extraction; human activity pattern visualisation; incremental statistical method; information visualisation; location sensors; smart home environment; spatiotemporal relations; spatiotemporal topology; ubiquitous smart space; user activity patterns;
  • fLanguage
    English
  • Journal_Title
    Communications, IET
  • Publisher
    iet
  • ISSN
    1751-8628
  • Type

    jour

  • DOI
    10.1049/iet-com.2010.0936
  • Filename
    6125455