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DISCO: Ultra-Lightweight Mobility Discovery

Published: 04 November 2018 Publication History

Abstract

Capturing individual mobility patterns has become a crucial issue for a tremendous number of applications, often requiring the use of privacy-invasive or energy-consuming sensors and online services. In parallel to this, the proliferation of wireless network access points (APs), scattered in a very dense manner in many geographical areas, is now opening up new technological opportunities. In this work, we demonstrate the use of network discovery data passively collected from Wi-Fi APs to infer mobility indicators. This local approach can potentially be implemented on any device with a communication interface, and allows for continuous and long-term data collection. The demo showcases a multi-platform mobile app (DISCO) and is presented alongside an extended desktop analysis toolbox. Additional material can be found online1.

References

[1]
Sébastien Faye, Walter Bronzi, Ibrahim Tahirou, and Thomas Engel. 2017. Characterizing User Mobility Using Mobile Sensing Systems. International Journal of Distributed Sensor Networks 13, 8 (2017).
[2]
Sébastien Faye, Ibrahim Tahirou, and Thomas Engel. 2016. Demo Abstract: Human Mobility Profiling Using Privacy-Friendly Wi-Fi and Activity Traces. In The 14th ACM Conference on Embedded Networked Sensor Systems (SenSys 2016). ACM, Stanford, CA, USA.
[3]
David Kofoed Wind, Piotr Sapiezynski, Magdalena Anna Furman, and Sune Lehmann. 2016. Inferring stop-locations from wifi. PloS one 11, 2 (2016), e0149105.
[4]
Mengyu Zhou, Minghua Ma, Yangkun Zhang, Kaixin SuiA, Dan Pei, and Thomas Moscibroda. 2016. EDUM: classroom education measurements via large-scale WiFi networks. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 316--327.

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  • (2019)SWAMProceedings of the 1st ACM International Workshop on Technology Enablers and Innovative Applications for Smart Cities and Communities10.1145/3364544.3364824(38-45)Online publication date: 13-Nov-2019
  1. DISCO: Ultra-Lightweight Mobility Discovery

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    cover image ACM Conferences
    SenSys '18: Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems
    November 2018
    449 pages
    ISBN:9781450359528
    DOI:10.1145/3274783
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 04 November 2018

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    • (2019)SWAMProceedings of the 1st ACM International Workshop on Technology Enablers and Innovative Applications for Smart Cities and Communities10.1145/3364544.3364824(38-45)Online publication date: 13-Nov-2019

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