WarnFi: non-invasive wifi-based abnormal activity sensing using non-parametric model

Pang, Na, Zhu, Dali, Li, Gang and Liu, Shaowu 2017, WarnFi: non-invasive wifi-based abnormal activity sensing using non-parametric model, in MILCOM 2017 : Proceedings of the 2017 IEEE Military Communications Conference, IEEE, Piscataway, N.J., pp. 800-805, doi: 10.1109/MILCOM.2017.8170747.

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Title WarnFi: non-invasive wifi-based abnormal activity sensing using non-parametric model
Formatted title WarnFi: non-invasive wifi-based abnormal activity sensing using non-parametric model
Author(s) Pang, Na
Zhu, Dali
Li, GangORCID iD for Li, Gang orcid.org/0000-0003-1583-641X
Liu, Shaowu
Conference name IEEE Military Communications. Conference (2017 : Baltimore, Md.)
Conference location Baltimore, Md.
Conference dates 2017/10/23 - 2017/10/25
Title of proceedings MILCOM 2017 : Proceedings of the 2017 IEEE Military Communications Conference
Editor(s) Unknown
Publication date 2017
Conference series IEEE Military Communications Conference
Start page 800
End page 805
Total pages 6
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) Sensors
Wireless communication
Wireless sensor networks
Wireless fidelity
Channel state information
Feature extraction
Cameras
Science & Technology
Technology
Telecommunications
ACTION RECOGNITION
ISBN 9781538605950
ISSN 2155-7586
Language eng
DOI 10.1109/MILCOM.2017.8170747
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2017, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30114188

Document type: Conference Paper
Collection: School of Information Technology
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