Cargando…
Tracking Human Mobility Using WiFi Signals
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 t...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489206/ https://www.ncbi.nlm.nih.gov/pubmed/26132115 http://dx.doi.org/10.1371/journal.pone.0130824 |
_version_ | 1782379310290567168 |
---|---|
author | Sapiezynski, Piotr Stopczynski, Arkadiusz Gatej, Radu Lehmann, Sune |
author_facet | Sapiezynski, Piotr Stopczynski, Arkadiusz Gatej, Radu Lehmann, Sune |
author_sort | Sapiezynski, Piotr |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4489206 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44892062015-07-14 Tracking Human Mobility Using WiFi Signals Sapiezynski, Piotr Stopczynski, Arkadiusz Gatej, Radu Lehmann, Sune PLoS One Research Article 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. Public Library of Science 2015-07-01 /pmc/articles/PMC4489206/ /pubmed/26132115 http://dx.doi.org/10.1371/journal.pone.0130824 Text en © 2015 Sapiezynski et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Sapiezynski, Piotr Stopczynski, Arkadiusz Gatej, Radu Lehmann, Sune Tracking Human Mobility Using WiFi Signals |
title | Tracking Human Mobility Using WiFi Signals |
title_full | Tracking Human Mobility Using WiFi Signals |
title_fullStr | Tracking Human Mobility Using WiFi Signals |
title_full_unstemmed | Tracking Human Mobility Using WiFi Signals |
title_short | Tracking Human Mobility Using WiFi Signals |
title_sort | tracking human mobility using wifi signals |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489206/ https://www.ncbi.nlm.nih.gov/pubmed/26132115 http://dx.doi.org/10.1371/journal.pone.0130824 |
work_keys_str_mv | AT sapiezynskipiotr trackinghumanmobilityusingwifisignals AT stopczynskiarkadiusz trackinghumanmobilityusingwifisignals AT gatejradu trackinghumanmobilityusingwifisignals AT lehmannsune trackinghumanmobilityusingwifisignals |