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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/15450

Title: WiFiPi: Involuntary Tracking of Visitors at Mass Events
Authors: BONNE, Bram
Barzan, Arno
QUAX, Peter
LAMOTTE, Wim
Issue Date: 2013
Publisher: IEEE
Citation: Proceedings of The 7th IEEE WoWMoM Workshop on Autonomic and Opportunistic Communications, p. 1-6
Abstract: To simulate crowds at mass events, realistic movement data of people is required. Despite their limited capacity for approximating real human mobility, synthetic movement models are traditionally used for this purpose. More realistic simulations can be achieved by using real-life movement data, gathered by observing people in the desired context. This paper presents a method for tracking people at mass events without the need for active cooperation by the subjects. The mechanism works by scanning at multiple locations for packets sent out by the Wi-Fi interface on visitors’ smartphones, and correlating the data captured at these different locations. The proposed method can be implemented at very low cost on Raspberry Pi computers. This implementation was trialed in two different contexts: a popular music festival and a university campus. 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 system.
URI: http://hdl.handle.net/1942/15450
ISBN: 978-1-4673-5828-6
Category: C1
Type: Proceedings Paper
Appears in Collections: Research publications

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