title: Tracking Human Mobility Using WiFi Signals.
abstract: We study six months of human mobility data, including WiFi and GPS traces recorded with high temporal resolution, and find that time series of WiFi scans contain a strong latent location signal. In fact, due to inherent stability and low entropy of human mobility, it is possible to assign location to WiFi access points based on a very small number of GPS samples and then use these access points as location beacons. Using just one GPS observation per day per person allows us to estimate the location of, and subsequently use, WiFi access points to account for 80% of mobility across a population. These results reveal a great opportunity for using ubiquitous WiFi routers for high-resolution outdoor positioning, but also significant privacy implications of such side-channel location tracking.
authors.affiliation: Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark.
authors.forename: Piotr
authors.initials: P
authors.lastname: Sapiezynski
authors.affiliation: Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark; Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States of America.
authors.forename: Arkadiusz
authors.initials: A
authors.lastname: Stopczynski
authors.affiliation: Department of Economics, University of Copenhagen, Copenhagen, Denmark.
authors.forename: Radu
authors.initials: R
authors.lastname: Gatej
authors.affiliation: Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark; Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.
authors.forename: Sune
authors.initials: S
authors.lastname: Lehmann
mesh_terms: D006801:Humans; D009068:Movement; D013686:Telemetry / Q000379:methods*