Abstract
We investigate the detection of activities and presence in the proximity of a mobile phone via the WiFi-RSSI at the phone. This is the first study to utilise RSSI in received packets at a mobile phone for the classification of activities. We discuss challenges that hinder the utilisation of WiFi PHY-layer information, recapitulate lessons learned and describe the hardware and software employed. Also, we discuss features for activity recognition (AR) based on RSSI and present two case studies. We make available our implemented tools for AR based on RSSI.
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CITATION STYLE
Sigg, S., Hock, M., Scholz, M., Tröster, G., Wolf, L., Ji, Y., & Beigl, M. (2014). Passive, Device-free recognition on your mobile phone: Tools, Features and a case study. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 131, pp. 435–446). Springer Verlag. https://doi.org/10.1007/978-3-319-11569-6_34
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