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Wi-Fi based city users behaviour analysis for smart city
Bellini P., Cenni D., Nesi P., Paoli I. Journal of Visual Languages and Computing42  31-45,2017.Type:Article
Date Reviewed: Mar 20 2018

The vision of a smart city capable of real-time adaptation to its citizens’ behaviors relies on the gathering of a huge amount of dynamic data. One possible venue for feeding the underlying information technology (IT) infrastructure of such cities is the already-existing Wi-Fi networks that enable all, locals as well as tourists and administrative personnel, to communicate. The locations of these network access points (APs) have been, up to now, chosen in an ad hoc manner; finding a methodology for the systematic and cost-effective selection of Wi-Fi APs is the goal of this paper.

The first part of this study uses the traces of taxi movements in San Francisco to assess different AP positioning techniques, in terms of infrastructure cost and prediction quality, when trying to determine the origin-destination matrices of these movements. The impact of these techniques can be compared visually, using an online tool developed by the authors. Without a clearly winning approach, a heuristic has been, in the second part of the paper, devised for Florence, Italy, to assess the flow of city users. Different analyses are performed using a finely selected subset of the Wi-Fi AP data linked to the “Florence, Where, What?” mobile app: heat maps, origin-destination matrices, and unusual pattern detection. This last application uses a time-of-day-dependent ARMA model to predict user movements, to be compared to actual data to perform early detection of unusual events.

I would recommend this easy-to-read paper to researchers interested in the practical applications of data analysis techniques for connected cities.

Reviewer:  P. Jouvelot Review #: CR145919 (1806-0316)
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Wireless Communication (C.2.1 ... )
 
 
Sensors (I.2.9 ... )
 
 
Social And Behavioral Sciences (J.4 )
 
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