Kumar Reddy, S.K.Naik, A.S.2026-02-062023Lecture Notes in Electrical Engineering, 2023, Vol.1023 LNEE, , p. 513-52118761100https://doi.org/10.1007/978-981-99-0969-8_53https://idr.nitk.ac.in/handle/123456789/29521The mining industry is well known for valuable minerals all over the world and the way to get minerals is by mining below the surface. Real-time monitoring of environmental parameters from underground mines is a very complex task to ensure safety. Accidents in the underground area are due to hazardous toxic gas spread beyond the threshold limit value at excavations. These mine gases are a threat to both mine workers’ health and the mine environment and are also very hard for miners to detect. Automation in the mining industry reduces hazardous accidents while improving efficiency and productivity. Adopting the Internet of Things (IoT) with Long Range (LoRa) wireless communication technology to build a robust long-range wireless communication system to monitor environmental parameters and hazardous events. To ensure a safe mine environment for mineworkers at the mine site, Artificial Intelligence techniques are an add-on to automation systems to build predictive modeling for an intelligent early warning alert system. However, current solutions are limited to monitoring, low computing power and processing capability, battery lifetime, suitable at the laboratory level, or reports events in a few cases. The proposed system is comprised of the IoT-based sensor modules, communication protocols, Long-Range (LoRa), and machine learning technologies to establish safe, reliable communication from the underground mine to the surface area. A reliable, robust, and cost-effective communication system should be required that monitors environmental parameters and predicts reports of unusual events by adopting new technology. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Environmental monitoringInternet of ThingsLoRaMachine learningUnderground mine