Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)

Contrastive Analysis for Human Activity Recognition Algorithms Using WiFi Signals

Authors
Jian Zhou, Han Su, Kai Yu
Corresponding Author
Jian Zhou
Available Online December 2016.
DOI
https://doi.org/10.2991/icwcsn-16.2017.65How to use a DOI?
Keywords
channel state information (CSI); dynamic time warping (DTW); earth mover distance (EMD); activity recognition
Abstract
Human Activity monitoring has become increasingly important and has the potential to support a wide area of applications including elder care, well-being management, fitness tracking and building surveillance. Traditional approaches involve wearable sensors and specialized hardware installations. Compared with these solutions, channel state information (CSI) has its advantage. The algorithm for human detection based on CSI Info has become increasingly important. Some prior WiFi signal based human activity recognition systems have been proposed such as Wisee[8], WiFall[11], Witrack[9], CARM[10]. Different from prior works, we propose a contrastive analysis for the recognition algorithms under different transmission frequencies and activities. Finally, the experimental performance of DTW (Dynamic Time Wrapping) and EMD (Earth Mover Distance) is adopted. Our works show that EMD has a better performance than DTW in most cases.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-302-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icwcsn-16.2017.65How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jian Zhou
AU  - Han Su
AU  - Kai Yu
PY  - 2016/12
DA  - 2016/12
TI  - Contrastive Analysis for Human Activity Recognition Algorithms Using WiFi Signals
PB  - Atlantis Press
SP  - 299
EP  - 303
SN  - 2352-538X
UR  - https://doi.org/10.2991/icwcsn-16.2017.65
DO  - https://doi.org/10.2991/icwcsn-16.2017.65
ID  - Zhou2016/12
ER  -