WiFiPi: Involuntary tracking of visitors at mass events

  title={WiFiPi: Involuntary tracking of visitors at mass events},
  author={B. Bonn{\'e} and A. Barzan and P. Quax and Wim Lamotte},
  journal={2013 IEEE 14th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)},
  • B. Bonné, A. Barzan, +1 author Wim Lamotte
  • Published 2013
  • Computer Science
  • 2013 IEEE 14th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)
  • To simulate crowds at mass events, realistic movement data of people is required. [...] Key Method The method allows for tracking thousands of people simultaneously, and achieves a higher coverage rate than similar methods for involuntary crowd tracking. Moreover, the coverage rate is expected to increase even further as more people will start using smartphones. The proposed method has many applications in different domains. It also entails privacy implications that must be considered when deploying a similar…Expand Abstract
    83 Citations
    WiFiPi-Tracking at mass events
    • P. Patil, A. Kokil
    • Computer Science
    • 2015 International Conference on Pervasive Computing (ICPC)
    • 2015
    • 10
    Presumably Simple: Monitoring Crowds Using WiFi
    • 26
    • PDF
    Crowd Mobility Analysis using WiFi Sniffers
    • 7
    • PDF
    Demonstrations and people-counting based on Wifi probe requests
    • Christin Groba
    • Computer Science
    • 2019 IEEE 5th World Forum on Internet of Things (WF-IoT)
    • 2019
    • 2
    • PDF
    Monitoring crowd condition in public spaces by tracking mobile consumer devices with wifi interface
    • 27
    • PDF
    Estimating Pedestrian Densities, Wait Times, and Flows with Wi-Fi and Bluetooth Sensors
    • 28
    • PDF
    Filters for Wi-Fi Generated Crowd Movement Data
    • 6
    • PDF
    Analyzing Pedestrian Flows Based on Wi-Fi and Bluetooth Captures


    Mapping the urban wireless landscape with Argos
    • 37
    • PDF
    Trace-based mobility modeling for multi-hop wireless networks
    • 109
    I know who you will meet this evening! Linking wireless devices using Wi-Fi probe requests
    • 67
    • PDF
    A survey of mobility models for ad hoc network research
    • 4,966
    • PDF
    CRAWDAD: a community resource for archiving wireless data at Dartmouth
    • 363
    • PDF
    Efficient location tracking using sensor networks
    • H. T. Kung, D. Vlah
    • Computer Science
    • 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003.
    • 2003
    • 293
    • PDF
    De-anonymizing Social Networks
    • 1,200
    • PDF
    The ONE simulator for DTN protocol evaluation
    • 715
    • PDF
    Human mobility characterization from cellular network data
    • 253
    • PDF