Passive Wi-Fi monitoring in the wild: a long-term study across multiple location typologies

Miguel Ribeiro; Nuno Nunes; Valentina Nisi; Johannes Schöning

doi:10.1007/s00779-020-01441-z

Passive Wi-Fi monitoring in the wild: a long-term study across multiple location typologies

Pers Ubiquitous Comput. 2022;26(3):505-519. doi: 10.1007/s00779-020-01441-z. Epub 2020 Sep 17.

Authors

Miguel Ribeiro¹, Nuno Nunes¹, Valentina Nisi², Johannes Schöning³

Affiliations

¹ Instituto Superior Téncico, ITI/LARSyS, ULisbon, Portugal.
² ITI/LARSyS, Universidade da Madeira, Funchal, Portugal.
³ Human-Computer Interaction, University of Bremen, ITI/LARSyS, Bremen, Germany.

Abstract

In this paper, we present a systematic analysis of large-scale human mobility patterns obtained from a passive Wi-Fi tracking system, deployed across different location typologies. We have deployed a system to cover urban areas served by public transportation systems as well as very isolated and rural areas. Over 4 years, we collected 572 million data points from a total of 82 routers covering an area of 2.8 km². In this paper we provide a systematic analysis of the data and discuss how our low-cost approach can be used to help communities and policymakers to make decisions to improve people's mobility at high temporal and spatial resolution by inferring presence characteristics against several sources of ground truth. Also, we present an automatic classification technique that can identify location types based on collected data.

Keywords: Mobility analysis; Passive sensing; Wi-Fi tracking.