Detecting intra-room mobility with signal strength descriptors

  • Authors:

  • Konstantinos Kleisouris;Bernhard Firner;Richard Howard;Yanyong Zhang;Richard P. Martin

  • Affiliations:

  • Rutgers University, Piscataway, NJ, USA;Rutgers University, North Brunswick, NJ, USA;Rutgers University, North Brunswick, NJ, USA;Rutgers University, North Brunswick, NJ, USA;Rutgers University, Piscataway, NJ, USA

  • Venue:
  • Proceedings of the eleventh ACM international symposium on Mobile ad hoc networking and computing
  • Year:
  • 2010

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Abstract

We explore the problem of detecting whether a device has moved within a room. Our approach relies on comparing summaries of received signal strength measurements over time, which we call descriptors. We consider descriptors based on the differences in the mean, standard deviation, and histogram comparison. In close to 1000 mobility events we conducted, our approach delivers perfect recall and near perfect precision for detecting mobility at a granularity of a few seconds. It is robust to the movement of dummy objects near the transmitter as well as people moving within the room. The detection is successful because true mobility causes fast fading, while environmental mobility causes shadow fading, which exhibit considerable difference in signal distributions. The ability to produce good detection accuracy throughout the experiments also demonstrates that our approach can be applied to varying room environments and radio technologies, thus enabling novel security, health care, and inventory control applications.