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Vega-Barbas M, Álvarez-Campana M, Rivera D, et al. AFOROS: A Low-Cost Wi-Fi-Based Monitoring System for Estimating Occupancy of Public Spaces. Sensors (Basel). 2021;21(11)doi: 10.3390/s21113863.
Vega-Barbas, M., Álvarez-Campana, M., Rivera, D., Sanz, M., & Berrocal, J. (2021). AFOROS: A Low-Cost Wi-Fi-Based Monitoring System for Estimating Occupancy of Public Spaces. Sensors (Basel, Switzerland), 21(11), . https://doi.org/10.3390/s21113863
Vega-Barbas, Mario, et al. "AFOROS: A Low-Cost Wi-Fi-Based Monitoring System for Estimating Occupancy of Public Spaces." Sensors (Basel, Switzerland) vol. 21,11 (2021). doi: https://doi.org/10.3390/s21113863
Vega-Barbas M, Álvarez-Campana M, Rivera D, Sanz M, Berrocal J. AFOROS: A Low-Cost Wi-Fi-Based Monitoring System for Estimating Occupancy of Public Spaces. Sensors (Basel). 2021 Jun 03;21(11). doi: 10.3390/s21113863. PMID: 34205031; PMCID: PMC8199860.
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Sensors (Basel). 2021 Jun 03;21(11). doi: 10.3390/s21113863.

AFOROS: A Low-Cost Wi-Fi-Based Monitoring System for Estimating Occupancy of Public Spaces.

Sensors (Basel, Switzerland)

Mario Vega-Barbas, Manuel Álvarez-Campana, Diego Rivera, Mario Sanz, Julio Berrocal

Affiliations

  1. ETSI de Telecomunicación, Universidad Politécnica de Madrid (UPM), Avda. Complutense 30, 28040 Madrid, Spain.

PMID: 34205031 PMCID: PMC8199860 DOI: 10.3390/s21113863

Abstract

Estimating the number of people present in a given venue in real-time is extremely useful from a security, management, and resource optimization perspective. This article presents the architecture of a system based on the use of Wi-Fi sensor devices that allows estimating, almost in real-time, the number of people attending an event that is taking place in a venue. The estimate is based on the analysis of the "probe request" messages periodically transmitted by smartphones to determine the existence of Wi-Fi access points in the vicinity. The method considers the MAC address randomization mechanisms introduced in recent years in smartphones, which prevents the estimation of the number of devices by simply counting different MAC addresses. To solve this difficulty, our Wi-Fi sensors analyze other fields present in the header of the IEEE 802.11 frames, the information elements, to extract a unique fingerprint from each smartphone. The designed system was tested in a set of real scenarios, obtaining an estimate of attendance at different public events with an accuracy close to 95%.

Keywords: Wi-Fi probe; Wi-Fi sensor; Wi-Fi tracking; automatic people counting; occupancy estimation; passive tracking

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