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RSS-based Device-free Passive Detection and Localization using Home Automation Network Radio Frequencies

This research provided a proof of concept for a device-free passive (DfP) system capable of detecting and localizing a target through exploitation of a home automation network’s radio frequency (RF) signals. The system was developed using Insteon devices with a 915 MHz center frequency. Without developer privileges, limitations of the Insteon technology like no intrinsic received signal strength (RSS) field and silent periods between messages were overcome by using software-defined radios to simulate Insteon devices capable of collecting and reporting RSS, and by creating a message generation script and implementing a calibrated filter threshold to reduce silent periods. Evaluation of the system deployment in a simple room with no furniture produced detection rates up to PD = 100% and false positive rates as low as PF = 1.6% for baseline threshold detection along the line of sight (LOS) in a simple tripwire setup. Signal attenuation of foam blocks at different distances along this LOS ranged from 2.2-4.4 dB. Cell-based fingerprinting for localization using multiple nodes in this room achieved accuracy only as high as P A = 5.4% and false positives only as low as PF = 88.3%. A context-based localization method was developed in response and was able to achieve P A = 28.3% and PF = 40.0%. The system was then deployed in a similar room containing several metal objects and achieved P A = 42.2% and PF = 0.0%. Deployment in a similar room with RF absorbent objects achieved P A = 23.3% and PF = 53.3%. Feasibility of exploiting RF of a home automation network for DfP indoor detection and localization was demonstrated. Despite not achieving optimal localization performance, the results showed promise for future DfP system deployment on top of home automation RF devices.