Can Future Wireless Networks Detect Fires?

Abstract

Latencies, operating ranges, and false positive rates for existing indoor fire detection systems like smoke detectors and sprinkler systems are far from ideal. This paper explores the use of wireless radio frequency (RF) signals to detect indoor fires with low latency, through walls and other occlusions. We build on past research focused on wireless sensing, and introduce RFire, a system which uses millimeter wave technology and deep learning to extract instances of fire. We perform line-of-sight (LoS) and occluded non-LoS experiments with fire at different distances, and find that RFire achieves a best-result mean latency of 24 seconds when trained and tested in multiple environments. RFire yields at least a 4 times improvement in mean alarm latency over today's alarms.