LAUSR

To improve driving safety and avoid accidents caused by driving fatigue, drowsiness detection aims to alarm the driver before he/she falls asleep. Since breathing rate is a key indicator of the drowsy state, respiration monitoring in the noisy driving environment is critical for developing an effective driving fatigue detection system. In this paper, we propose, for the first time, an RFID based respiration monitoring system for driving environments. The system estimates the respiration rate of a driver based on phase values sampled from multiple RFID tags attached to the seat belt, while exploiting the tag diversity to combat the strong noise in the driving environment. Both tensor completion and tensor Canonical Polyadic Decomposition (CPD) are applied to process the phase values, to overcome the influence of frequency hopping, random sampling, vehicle vibration, and other environmental movements. The proposed system is analyzed and implemented with commodity RFID devices. Its accurate and robust performance is demonstrated with extensive experiments conducted in a real driving car.