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Demo Abstract: Human Mobility Profiling Using Privacy-Friendly Wi-Fi and Activity Traces
Faye, Sébastien; Tahirou, Ibrahim; Engel, Thomas
2016In Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems (SenSys 2016)
Peer reviewed
 

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Keywords :
Human Mobility Profiling; Sensing Systems; Graph Theory
Abstract :
[en] Human mobility is one of the key topics to be considered in the networks of the future, both by industrial and research communities that are already focused on multidisciplinary applications and user-centric systems. If the rapid proliferation of networks and high-tech miniature sensors makes this reality possible, the ever-growing complexity of the metrics and parameters governing such systems raises serious issues in terms of privacy, security and computing capability. In this demonstration, we show a new system, able to estimate a user's mobility profile based on anonymized and lightweight smartphone data. In particular, this system is composed of (1) a web analytics platform, able to analyze multimodal sensing traces and improve our understanding of complex mobility patterns, and (2) a smartphone application, able to show a user's profile generated locally in the form of a spider graph. In particular, this application uses anonymized and privacy-friendly data and methods, obtained thanks to the combination of Wi-Fi traces, activity detection and graph theory, made available independent of any personal information.
Research center :
SnT
Disciplines :
Computer science
Author, co-author :
Faye, Sébastien ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Tahirou, Ibrahim ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Engel, Thomas ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
External co-authors :
no
Language :
English
Title :
Demo Abstract: Human Mobility Profiling Using Privacy-Friendly Wi-Fi and Activity Traces
Publication date :
14 November 2016
Event name :
The 14th ACM Conference on Embedded Networked Sensor Systems (SenSys 2016)
Event organizer :
ACM
Event place :
Stanford, United States
Event date :
from 14-11-2016 to 16-11-2016
Audience :
International
Main work title :
Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems (SenSys 2016)
Peer reviewed :
Peer reviewed
FnR Project :
FNR5825301 - Multimodal Mobility Assistance, 2013 (01/04/2014-31/03/2017) - Thomas Engel
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