Revisiting Indoor Intrusion Detection With WiFi Signals: Do Not Panic Over a Pet!

Indoor intrusion detection (IID) is an essential technology to enable various important applications. Recently, an extensive amount of research has been carried out to develop device-free intrusion detection systems based on the WiFi signal due to its ubiquitous existence and minimum privacy disclosure. However, existing WiFi-based intrusion detection systems typically suffer from false alarms caused by pets, limiting their usage in practice. In this article, we propose PetFree to revisit the IID problem with careful consideration of pet interference. PetFree uses fine-grained channel state information (CSI) of WiFi signals to detect whether there is a human or a pet in the monitoring area. The basic idea of PetFree is to use the effective interference height (EIH) differences between humans and pets. We propose a novel CSI-EIH model to characterize the relationship between CSI measurements and the EIH of the target. Based on this model, PetFree manages to achieve accurate pet identification using only a single WiFi link. We implement and evaluate PetFree extensively with commodity WiFi devices in three different indoor scenarios. Results show that PetFree achieves an overall 93.7% intrusion detection rate and decreases the false alarm rate caused by home pets to 6.5%, significantly outperforming the state-of-the-art approach.