TY - GEN
T1 - A WiFi-based home security system
AU - Zhang, Shaohu
AU - Venkatnarayan, Raghav H.
AU - Shahzad, Muhammad
PY - 2020
Y1 - 2020
N2 - Typical home security systems monitor homes for intrusions by installing contact sensors on doors and windows and motion sensors inside the house. Unfortunately, due to the high deployment and operational costs of today's home security systems, only a small fraction of homes have security systems installed (e.g., only 17% in the US and 15% in China). In this paper, we propose a Wi Fi based H ome S ecurity system (WiHS) that uses commodity WiFi devices, which most modern households already have, to perform the three primary tasks of typical home security systems: 1) detect when a door/window is opened/closed, 2) identify which door/window has been opened/closed, and 3) detect movements inside the house. The design of WiHS is based on our intuitive and theoretical understanding of the impacts of the movements of doors and windows on WiFi signals, which we will develop and present in this paper. We extensively evaluated WiHS using commodity WiFi devices in 3 different houses. WiHS detected intrusions with over 95% accuracy and identified the exact door/window that moved with just 4.5% average error.
AB - Typical home security systems monitor homes for intrusions by installing contact sensors on doors and windows and motion sensors inside the house. Unfortunately, due to the high deployment and operational costs of today's home security systems, only a small fraction of homes have security systems installed (e.g., only 17% in the US and 15% in China). In this paper, we propose a Wi Fi based H ome S ecurity system (WiHS) that uses commodity WiFi devices, which most modern households already have, to perform the three primary tasks of typical home security systems: 1) detect when a door/window is opened/closed, 2) identify which door/window has been opened/closed, and 3) detect movements inside the house. The design of WiHS is based on our intuitive and theoretical understanding of the impacts of the movements of doors and windows on WiFi signals, which we will develop and present in this paper. We extensively evaluated WiHS using commodity WiFi devices in 3 different houses. WiHS detected intrusions with over 95% accuracy and identified the exact door/window that moved with just 4.5% average error.
UR - https://dx.doi.org/10.1109/MASS50613.2020.00026
U2 - 10.1109/mass50613.2020.00026
DO - 10.1109/mass50613.2020.00026
M3 - Conference contribution
BT - 17th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2020
ER -