Does Location Help Daily Activity Recognition?

  • Chao Chen
  • Daqing Zhang
  • Lin Sun
  • Mossaab Hariz
  • Yang Yuan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7251)


Daily activity recognition is essential to enable smart elderly care services and the recognition accuracy affects much the quality of the elderly care system. Although a lot of work has been done to recognize elderly people’s activities of daily life (ADL), few systems have investigated if the location information can be deployed to improve the ADL recognition accuracy. In this paper, we intend to incorporate the location information in the activity recognition algorithm and see if it can help to improve the recognition accuracy. We propose two ways to bring the location information into the picture: one way is to bring location in the feature level, the other way is to utilize it to filter irrelevant sensor readings. Intensive experiments have been conducted to show that bringing location information into the activity recognition algorithm in both ways can help to improve the recognition rate by around 5% on average compared to the system neglecting the location information.


Elderly People Location Information Recognition Accuracy Activity Recognition Smart Home 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Chao Chen
    • 1
  • Daqing Zhang
    • 1
  • Lin Sun
    • 1
  • Mossaab Hariz
    • 1
  • Yang Yuan
    • 2
  1. 1.CNRS SAMOVARInstitut TELECOM/TELECOM SudParisFrance
  2. 2.School of ComputerNorthwestern Polytechnical UniversityChina

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