Passive, Device-Free Recognition on Your Mobile Phone: Tools, Features and a Case Study

Stephan Sigg; Mario Hock; Markus Scholz; Gerhard Tröster; Lars Wolf; Yusheng Ji; Michael Beigl

Mobile and Ubiquitous Systems: Computing, Networking, and Services. 10th International Conference, MOBIQUITOUS 2013, Tokyo, Japan, December 2-4, 2013, Revised Selected Papers

Research Article

Passive, Device-Free Recognition on Your Mobile Phone: Tools, Features and a Case Study

Download

456 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-319-11569-6_34,
    author={Stephan Sigg and Mario Hock and Markus Scholz and Gerhard Tr\o{}ster and Lars Wolf and Yusheng Ji and Michael Beigl},
    title={Passive, Device-Free Recognition on Your Mobile Phone: Tools, Features and a Case Study},
    proceedings={Mobile and Ubiquitous Systems: Computing, Networking, and Services. 10th International Conference, MOBIQUITOUS 2013, Tokyo, Japan, December 2-4, 2013,  Revised Selected Papers},
    proceedings_a={MOBIQUITOUS},
    year={2014},
    month={12},
    keywords={Activity recognition Passive device-free recognition},
    doi={10.1007/978-3-319-11569-6_34}
}

Stephan Sigg
Mario Hock
Markus Scholz
Gerhard Tröster
Lars Wolf
Yusheng Ji
Michael Beigl
Year: 2014
Passive, Device-Free Recognition on Your Mobile Phone: Tools, Features and a Case Study
MOBIQUITOUS
Springer
DOI: 10.1007/978-3-319-11569-6_34

Stephan Sigg¹^,*, Mario Hock²^,*, Markus Scholz³^,*, Gerhard Tröster⁴^,*, Lars Wolf¹^,*, Yusheng Ji⁵^,*, Michael Beigl³^,*

1: TU Braunschweig
2: Karlsruhe Institute of Technology
3: KIT
4: ETH Zurich
5: National Institute of Informatics

*Contact email: sigg@ibr.cs.tu-bs.de, mario.hock@student.kit.edu, scholz@teco.edu, troester@ife.ee.ethz.ch, wolf@ibr.cs.tu-bs.de, kei@nii.ac.jp, michael@teco.edu

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.

Keywords: Activity recognition Passive device-free recognition

Published: 2014-12-10

: http://dx.doi.org/10.1007/978-3-319-11569-6_34