• DocumentCode
    693519
  • Title

    Demo abstract: A radio tomographic system for real-time multiple people tracking

  • Author

    Bocca, Maurizio ; Kaltiokallio, Ossi ; Patwari, Neal

  • Author_Institution
    ECE Dept., Univ. of Utah, Salt Lake City, UT, USA
  • fYear
    2013
  • fDate
    8-11 April 2013
  • Firstpage
    305
  • Lastpage
    306
  • Abstract
    A radio tomographic (RT) system uses the received signal strength (RSS) measurements collected on the links of a wireless mesh network composed of low-power transceivers in order to form real-time images of the attenuation field of the monitored area. These images indicate the position of people, without requiring them to participate in the localization effort by wearing or carrying any electronic device. Accurate localization and tracking of multiple people in real-time is required in several real-world applications, such as ambient-assisted living, tactical operations, and pedestrian traffic analysis in stores. In these scenarios, RT systems must perform reliably also a) when the number of targets is not known a priori and varies over time, and b) when people interact, i.e., have intersecting trajectories, in the monitored area. We demonstrate a RT system which tackles all of these challenges and provides accurate tracking of a varying and unknown number of people (both stationary and mobile) in real-time.
  • Keywords
    computerised tomography; object tracking; radio links; radio transceivers; sensor placement; wireless mesh networks; RSS measurement; RT systems; attenuation field; electronic device; low-power transceivers; people localisation; radio tomographic imaging system; real-time people tracking; received signal strength; wireless mesh network links; Educational institutions; Monitoring; Real-time systems; Target tracking; Tomography; Trajectory; Transceivers; Device-free localization; Multiple target tracking; Radio tomography; Received signal strength;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Processing in Sensor Networks (IPSN), 2013 ACM/IEEE International Conference on
  • Conference_Location
    Philadelphia, PA
  • Type

    conf

  • DOI
    10.1109/IPSN.2013.6917556
  • Filename
    6917556