Demo abstract: DISCO – Ultra-lightweight mobility discovery

Auteurs

S. Faye, F. Melakessou, and D. Khadraoui

Référence

in the 16th ACM Conference on Embedded Networked Sensor Systems, SENSYS 2018, Shenzhen, China, 4-7 November 2018, ISBN: 978-145035952-8, pp. 341-342, 2018

Description

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 online.

Lien

doi:10.1145/3274783.3275173

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