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General Information
    • ISSN: 2010-3751
    • Frequency: Bimonthly (2012-2016); Quarterly (Since 2017)
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Mohamed Othman
    • Executive Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: Google Scholar, Engineering & Technology Digital Library, and Crossref, DOAJ, Electronic Journals LibraryEI (INSPEC, IET).
    • E-mail:  ijfcc@ejournal.net 
Editor-in-chief
Prof. Mohamed Othman
Department of Communication Technology and Network Universiti Putra Malaysia, Malaysia
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.
IJFCC 2016 Vol.5(4): 180-186 ISSN: 2010-3751
doi: 10.18178/ijfcc.2016.5.4.468

Device-Free Home Intruder Detection and Alarm System Using Wi-Fi Channel State Information

Mohammed Abdulaziz Aide Al-qaness, Fangmin Li, Xiaolin Ma, and Guo Liu
Abstract—In this paper, we design a device-free intruder detection and alarm system, named WiGarde by exploiting off-the-shelf Wi-Fi channel state information (CSI) to detect an intruder through door or window. WiGarde extracts the CSI amplitude information across MIMO antennas. We implemented WiGarde with commercial IEEE 802.11 NICs and evaluated its performance in two cluttered indoor environments. The system is robust and avoids false alarm occurrence, owing to our novel bad stream elimination algorithm. To extract the best feature, we design a new method to intercept the segment of the signal of intrusion based on wavelet analysis and dynamic time window based on Short-time Energy. We adopt Support Vector Machine (SVM) algorithm to classify human intrusion; our SVM algorithm could classify intrusion process with general walking through the area of interest. We compare WiGarde with the previous approaches; results show that our system outperforms the corresponding best CSI-based and RSSI-based in both of static and motion states. Our system gained high accuracy of 94.5% in a dynamic environment for intrusion through door or window.

Index Terms—Intruder detection, device-free, CSI, home safety motion detection, WiFi.

Mohammed Abdulaziz Aide Al-qaness is with the School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China (e-mail: alqaness@whut.edu.cn).
Fangmin Li is also now with Department of Mathematics and Computer Science, Changsha University, Changsha, 410022, China (e-mail: lfm@ccsu.edu.cn).
Xiaolin Ma and Guo Liu are with the School of Information Engineering, Wuhan University of Technology, China.

[PDF]

Cite: Mohammed Abdulaziz Aide Al-qaness, Fangmin Li, Xiaolin Ma, and Guo Liu, "Device-Free Home Intruder Detection and Alarm System Using Wi-Fi Channel State Information," International Journal of Future Computer and Communication vol. 5, no. 4, pp. 180-186, 2016.

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