ue 15(4): e4

Research Article

Analyzing Pedestrian Flows Based on Wi-Fi and Bluetooth Captures

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  • @ARTICLE{10.4108/ue.1.4.e4,
        author={Lorenz Schauer and Martin Werner},
        title={Analyzing Pedestrian Flows Based on Wi-Fi and Bluetooth Captures},
        journal={EAI Endorsed Transactions on Ubiquitous Environments},
        volume={1},
        number={4},
        publisher={ICST},
        journal_a={UE},
        year={2015},
        month={5},
        keywords={crowd density, pedestrian flow, tracking, Wi-Fi probes, Bluetooth},
        doi={10.4108/ue.1.4.e4}
    }
    
  • Lorenz Schauer
    Martin Werner
    Year: 2015
    Analyzing Pedestrian Flows Based on Wi-Fi and Bluetooth Captures
    UE
    ICST
    DOI: 10.4108/ue.1.4.e4
Lorenz Schauer1,*, Martin Werner1
  • 1: Ludwig-Maximilians-Universität München (LMU Munich), Mobile and Distributed Systems Group, Oettingenstr. 67, 80538 Munich, Germany
*Contact email: lorenz.schauer@ifi.lmu.de

Abstract

The rapid deployment of smartphones has led to a wide adoption of wireless communication systems such as Wi-Fi and Bluetooth. Both techniques leak information to the surroundings during operation. This information has been used in literature for estimating pedestrian flows, b ut t he c orrelation t o g round truth has not yet been evaluated. Thus, a reliable deployment in real world scenarios is rather difficult. To fill in this gap, we use ground truth provided by the security check process at a major airport and evaluate the quality of crowd information gathered from Wi-Fi and Bluetooth captures. We analyze estimated pedestrian flows and present three approaches improving the accuracy compared to a naive count of captured MAC addresses. Such counts only showed an impractical Pearson correlation of 0.53 for Bluetooth and 0.61 for Wi-Fi. The presented approaches yield a better correlation and allow for a practical estimation of pedestrian flows.