• DocumentCode
    2298794
  • Title

    Human Activity Inference for Ubiquitous RFID-Based Applications

  • Author

    Xiong, Jingwen ; Seet, Boon-Chong ; Symonds, Judith

  • Author_Institution
    Sch. of Comput. & Math. Sci., Auckland Univ. of Technol., Auckland, New Zealand
  • fYear
    2009
  • fDate
    7-9 July 2009
  • Firstpage
    304
  • Lastpage
    309
  • Abstract
    Radio frequency identification (RFID) is an important enabling technology for context-awareness in ubiquitous computing. RFID technology with complementary sensors is widely considered as a very promising approach to realizing the vision of ambient assisted living (AAL), which is an emerging application class in the domain of ubiquitous healthcare services. At the core of any assisted living systems is the important function of human activity inference, which is what enables such systems to be intelligently perceptive and responsive to the humans under their care. In this paper, we review the current state-of-the-art in activity inference for RFID-based applications, and present our ongoing work on a RFID-based assisted living prototype for `goal training´ or brain rehabilitation of patients with cognitive impairment in their home environments, with a discussion on the potential design issues involved.
  • Keywords
    health care; inference mechanisms; radiofrequency identification; ubiquitous computing; ambient assisted living; brain rehabilitation; cognitive impairment; context-awareness; goal training; human activity inference; radio frequency identification; ubiquitous RFID-based applications; ubiquitous computing; ubiquitous healthcare services; Conferences; Humans; Pervasive computing; Applications; Assisted Living; Healthcare; Human activity inference; RFID;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ubiquitous, Autonomic and Trusted Computing, 2009. UIC-ATC '09. Symposia and Workshops on
  • Conference_Location
    Brisbane, QLD
  • Print_ISBN
    978-1-4244-4902-6
  • Electronic_ISBN
    978-0-7695-3737-5
  • Type

    conf

  • DOI
    10.1109/UIC-ATC.2009.22
  • Filename
    5319219