Crowd sensing in indoor areas is becoming more and more fundamental for flow management, security and surveillance, or building usage statistics. This paper deals with a simple crowd sensing approach, which opportunistically exploits the already deployed WiFi networks, thus avoiding dedicated wiring and installations. The proposed algorithm is based on a two-step procedure that first applies a Wavelet decomposition of the signal strength data and then exploits the obtained coefficients to learn the unknown relation between crowd presence and signal changes. To this end, a customized learning-by-example (LBE) algorithm is trained for successive real-time crowd detection. The results of the experimental validation are presented to assess system potentialities and current limitations.
Opportunistic crowd sensing in WiFi-enabled indoor areas / Robol, Fabrizio; Viani, Federico; Polo, Alessandro; Giarola, Enrico; Garofalo, Paola; Zambiasi, Cristian; Massa, Andrea. - STAMPA. - (2015), pp. 274-275. (Intervento presentato al convegno Proc. 2015 IEEE AP-S tenutosi a Vancouver nel July 19-25, 2015) [10.1109/APS.2015.7304523].
Opportunistic crowd sensing in WiFi-enabled indoor areas
Robol, Fabrizio;Viani, Federico;Polo, Alessandro;Giarola, Enrico;Garofalo, Paola;Zambiasi, Cristian;Massa, Andrea
2015-01-01
Abstract
Crowd sensing in indoor areas is becoming more and more fundamental for flow management, security and surveillance, or building usage statistics. This paper deals with a simple crowd sensing approach, which opportunistically exploits the already deployed WiFi networks, thus avoiding dedicated wiring and installations. The proposed algorithm is based on a two-step procedure that first applies a Wavelet decomposition of the signal strength data and then exploits the obtained coefficients to learn the unknown relation between crowd presence and signal changes. To this end, a customized learning-by-example (LBE) algorithm is trained for successive real-time crowd detection. The results of the experimental validation are presented to assess system potentialities and current limitations.File | Dimensione | Formato | |
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Opportunistic crowd sensing in WiFi-enabled indoor areas.pdf
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