PRIVA'MOV: Analysing Human Mobility Through Multi-Sensor Datasets - Laboratoire d’Excellence Intelligences des Mondes Urbains Accéder directement au contenu
Communication Dans Un Congrès Année : 2017

PRIVA'MOV: Analysing Human Mobility Through Multi-Sensor Datasets

Résumé

The wide adoption of mobile devices has created unprecedented opportunities to collect mobility traces and make them available for the research community to conduct interdisciplinary research. However, mobility traces available in the public domain are usually restricted to traces resulting from a single sensor (e.g., either GPS, GSM or WiFi). In this paper, we present the PRIVA'MOV dataset, a novel dataset collected in the city of Lyon, France on which user mobility has been collected using multiple sensors. More precisely, this dataset contains mobility traces of about 100 persons including university students, staff and their family members over 15 months collected through the GPS, WiFi, GSM, and accelerometer sensors. We provide in this paper both a quantitative and a preliminary qualitative analysis of this dataset. Specifically, we report the number of visited points of interests, GSM antennas and WiFi hotspots and their distribution across the various users. We finally analyse the uniqueness of human mobility by considering the various sensors.
Fichier principal
Vignette du fichier
main.pdf (2.61 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01578557 , version 1 (29-08-2017)

Identifiants

  • HAL Id : hal-01578557 , version 1

Citer

Sonia Ben Mokhtar, Antoine Boutet, Louafi Bouzouina, Patrick Bonnel, Olivier Brette, et al.. PRIVA'MOV: Analysing Human Mobility Through Multi-Sensor Datasets. NetMob 2017, Apr 2017, Milan, Italy. ⟨hal-01578557⟩
2102 Consultations
638 Téléchargements

Partager

Gmail Facebook X LinkedIn More