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|Title: ||WiFiPi: Involuntary Tracking of Visitors at Mass Events|
|Authors: ||BONNE, Bram|
|Issue Date: ||2013|
|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.|
|Type: ||Proceedings Paper|
|Appears in Collections: ||Research publications|
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