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CoenoSense: A Framework for Real-Time Detection and Visualization of Collective Behaviors in Human Crowds by Tracking Mobile Devices

  • Martin Wirz
  • Tobias Franke
  • Eve Mitleton-Kelly
  • Daniel Roggen
  • Paul Lukowicz
  • Gerhard Tröster
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

There is a need for event organizers and emergency response personnel to detect emerging, potentially critical crowd situations at an early stage during city-wide mass gatherings. In this work, we present a framework to infer and visualize crowd behavior patterns in real-time from pedestrians’ GPS location traces. We deployed and tested our framework during the 2011 Lord Mayor’s Show in London. To collection location updates from festival visitors, a mobile phone app that supplies the user with event-related information and periodically logs the device’s location was distributed. We collected around four million location updates from over 800 visitors. The City of London Police consulted the crowd condition visualization to monitor the event. We learned from the police officers that our framework helps to assess occurring crowd conditions and to spot critical situations faster compared to the traditional video-based methods. With that, appropriate measure can be deployed quickly helping to resolve a critical situation at an early stage.

Keywords

Mobile Phone Location Update Crowd Condition Crowd Behavior Crowd Density 
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.

Notes

Acknowledgements

This work is supported under the FP7 ICT Future Enabling Technologies Programme under grant agreement No. 231288 (SOCIONICAL).

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Martin Wirz
    • 1
  • Tobias Franke
    • 2
  • Eve Mitleton-Kelly
    • 3
  • Daniel Roggen
    • 1
  • Paul Lukowicz
    • 2
  • Gerhard Tröster
    • 1
  1. 1.Wearable Computing LaboratoryETH ZürichZürichSwitzerland
  2. 2.Embedded IntelligenceDFKI KaiserslauternKaiserslauternGermany
  3. 3.Complexity Research ProgrammeLSELondonUK

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