Lessons learned using wi-fi and Bluetooth as means to monitor public service usage

BAI, Lu, IRESON, Neil, MAZUMDAR, Suvodeep and CIRAVEGNA, Fabio (2017). Lessons learned using wi-fi and Bluetooth as means to monitor public service usage. In: LEE, Seungyon, TAKAYAMA, Leila and TRUONG, Khai, (eds.) Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. New York, ACM, 432-440.

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Official URL: https://dl.acm.org/citation.cfm?id=3124417&CFID=10...
Link to published version:: https://doi.org/10.1145/3123024.3124417
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    Abstract

    Facets of urban public transport such as occupancy, waiting times, route preferences are essential to help deliver improved services as well as better information for passengers to plan their daily travel. The ability to automatically estimate passenger occupancy in near real-time throughout cities will be a step change in the way public service usage is currently estimated and provide significant insights to decision makers. The ever-increasing popularity and abundance of mobile devices with always-on Wi-Fi/Bluetooth interfaces makes Wi-Fi/Bluetooth sensing a promising approach for estimating passenger load. In this paper, we present a Wi-Fi/Bluetooth sensing system to detect mobile devices for estimating passenger counts using public transport. We present our findings on an initial set of experiments on a series of bus/tram journeys encapsulating different scenarios over five days in a UK metropolitan area. Our initial experiments show promising results and we present our plans for future large-scale experiments.

    Item Type: Book Section
    Additional Information: Paper presented at the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers, September 11-15, 2017, Maui, Hawaii, USA.
    Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
    Identification Number: https://doi.org/10.1145/3123024.3124417
    Page Range: 432-440
    Depositing User: Suvodeep Mazumdar
    Date Deposited: 18 Jan 2018 11:23
    Last Modified: 18 Jan 2018 11:23
    URI: http://shura.shu.ac.uk/id/eprint/16918

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