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Poster: A Low Cost People Flow Monitoring System For Sensing The Potential Danger

Published:07 September 2015Publication History

ABSTRACT

For a long history, stampede is one of the high potential disaster when thousands of people gathered. Current monitoring systems, however, can only detect the presence of a small number of sparsely located targets, rather than to monitor the change of people flow where there are large number of dense crowd in the environment. This paper presents DanSen, a low-cost people flow monitoring system for sensing the potential danger using the existing wifi infrastructures. Inspired by the dynamic light scattering (DLS) theory, the designed DanSen calculates the correlations between the initial channel state information (CSI) data and all the history CSI data to monitor the changes of people flow and also estimates the sharpness of the changes. By doing so, DanSen can be utilised to perceive the potential danger. Real-world experimental results illustrate the advantage and effectiveness of DanSen.

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  1. Poster: A Low Cost People Flow Monitoring System For Sensing The Potential Danger

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    • Published in

      cover image ACM Conferences
      MobiCom '15: Proceedings of the 21st Annual International Conference on Mobile Computing and Networking
      September 2015
      638 pages
      ISBN:9781450336192
      DOI:10.1145/2789168

      Copyright © 2015 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 September 2015

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      Acceptance Rates

      MobiCom '15 Paper Acceptance Rate38of207submissions,18%Overall Acceptance Rate440of2,972submissions,15%

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