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.
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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.
