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Open AccessArticle

Device-Free Indoor Activity Recognition System

Key Laboratory of Fiber Optical Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China
School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China
Department of Mathematics and Computer Science, Changsha University, Changsha 410022, China
Author to whom correspondence should be addressed.
Academic Editors: Plamen Angelov and José Antonio Iglesias Martínez
Appl. Sci. 2016, 6(11), 329;
Received: 11 September 2016 / Revised: 23 October 2016 / Accepted: 28 October 2016 / Published: 1 November 2016
(This article belongs to the Special Issue Human Activity Recognition)
In this paper, we explore the properties of the Channel State Information (CSI) of WiFi signals and present a device-free indoor activity recognition system. Our proposed system uses only one ubiquitous router access point and a laptop as a detection point, while the user is free and neither needs to wear sensors nor carry devices. The proposed system recognizes six daily activities, such as walk, crawl, fall, stand, sit, and lie. We have built the prototype with an effective feature extraction method and a fast classification algorithm. The proposed system has been evaluated in a real and complex environment in both line-of-sight (LOS) and none-line-of-sight (NLOS) scenarios, and the results validate the performance of the proposed system. View Full-Text
Keywords: activity recognition; device-free; CSI; wireless sensing; WiFi activity recognition; device-free; CSI; wireless sensing; WiFi
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MDPI and ACS Style

Al-qaness, M.A.A.; Li, F.; Ma, X.; Zhang, Y.; Liu, G. Device-Free Indoor Activity Recognition System. Appl. Sci. 2016, 6, 329.

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