Conference paper, Creative achievement

DISCO: Ultra-Lightweight Mobility Discovery

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.

Reference

  • [DOI] S. Faye, F. Melakessou, and D. Khadraoui, “DISCO: Ultra-Lightweight Mobility Discovery,” in The 16th ACM Conference on Embedded Networked Sensor Systems (SenSys 2018), Shenzhen, China, 2018.
    @inproceedings{SF-SENSYS-DEMO-18,
    Address = {Shenzhen, China},
    Author = {S{\'e}bastien Faye and Foued Melakessou and Djamel Khadraoui},
    Booktitle = {The 16th ACM Conference on Embedded Networked Sensor Systems (SenSys 2018)},
    Doi = {10.1145/3274783.3275173},
    Month = nov,
    Organization = {ACM},
    Title = {DISCO: Ultra-Lightweight Mobility Discovery},
    Year = {2018},
    Bdsk-Url-1 = {http://dx.doi.org/10.1145/3274783.3275173}}