MineSOS: Long-Range LoRa-Based Distress Gesture Sensing for Coal Mine Rescue

Abstract

AbstractDistress signal identification has great significance in saving lives in coal mine rescue. In response to the rescue in the long-distance coal mine tunnel full of dust and dangerous gas, we propose a distress gesture sensing system utilizing LoRa technology, called MineSOS. Inspired by the Morse code “SOS” and binary code, we first present a set of distress gestures with an error-check design, only requiring one hand movement. For signal processing, we propose a novel metric to choose the optimal LoRa attribute due to the observation of the complementary relationship between amplitude and phase variation. Finally, a double-check mechanism is presented to recognize and verify the distress information. We conducted extensive experiments to evaluate MineSOS’s performance, and results show that it can achieve high accuracy for gesture recognition in a coal mine lab. MineSOS system also has the capability of long-range sensing, which is believed to benefit emergency coal mine rescue.KeywordsLoRaDistress gesture recognitionCoal mine rescue