TY - JOUR
T1 - AudioGuard
T2 - omnidirectional indoor intrusion detection using audio device
AU - Wang, Tianben
AU - Li, Zhangben
AU - Yan, Honghao
AU - Liu, Xiantao
AU - Liu, Boqin
AU - Li, Shengjie
AU - Ma, Zhongyu
AU - Hu, Jin
AU - Zhang, Daqing
AU - Gu, Tao
PY - 2024/2
Y1 - 2024/2
N2 - Indoor intrusion detection is a critical task for home security. Previous works in intrusion detection suffer from the problems such as blind spots in non-line-of-sight (NLOS) areas, restricted device locations, massive offline training required, and privacy concern. In this article, we design and implement an omnidirectional indoor intrusion detection system, named AudioGuard, using only a pair of speaker and microphone. Au- dioGuard is able to detect both line-of-sight (LOS) and NLOS intrusions. Our observation of acoustic signal propagation in an indoor environment shows that there exist abundant multipath reflections and human movement introduces Doppler shift in echo signals. We hence capture periodical Doppler shift caused by intruder's walking motion to detect intrusion. Specifically, we first extract the Doppler shift embedded in echo signals, and we then propose a periodicity polarization method to cancel out the impact of the change of radial angle and the distance on periodicity of Doppler shift. Finally, we detect intrusion by measuring periodicity of Doppler shift over time. Extensive experiments show that AudioGuard achieves a miss report rate of 0% and 1.75% for LOS and NLOS intrusion, respectively, and a false alarm rate of 4.17%.
AB - Indoor intrusion detection is a critical task for home security. Previous works in intrusion detection suffer from the problems such as blind spots in non-line-of-sight (NLOS) areas, restricted device locations, massive offline training required, and privacy concern. In this article, we design and implement an omnidirectional indoor intrusion detection system, named AudioGuard, using only a pair of speaker and microphone. Au- dioGuard is able to detect both line-of-sight (LOS) and NLOS intrusions. Our observation of acoustic signal propagation in an indoor environment shows that there exist abundant multipath reflections and human movement introduces Doppler shift in echo signals. We hence capture periodical Doppler shift caused by intruder's walking motion to detect intrusion. Specifically, we first extract the Doppler shift embedded in echo signals, and we then propose a periodicity polarization method to cancel out the impact of the change of radial angle and the distance on periodicity of Doppler shift. Finally, we detect intrusion by measuring periodicity of Doppler shift over time. Extensive experiments show that AudioGuard achieves a miss report rate of 0% and 1.75% for LOS and NLOS intrusion, respectively, and a false alarm rate of 4.17%.
KW - Indoor intrusion detection
KW - acoustic sensing
KW - periodic doppler shift
UR - http://www.scopus.com/inward/record.url?scp=85183326601&partnerID=8YFLogxK
U2 - 10.1145/3625305
DO - 10.1145/3625305
M3 - Article
AN - SCOPUS:85183326601
SN - 2577-6207
VL - 5
SP - 1
EP - 22
JO - ACM Transactions on Internet of Things
JF - ACM Transactions on Internet of Things
IS - 1
M1 - 4
ER -