基于LoRa与HMM的煤矿安全监测系统设计

Design of Safety Monitoring System for Coal Mine Based on LoRa and HMM

针对煤矿生产开采中的安全问题,设计了基于LoRa技术与隐马尔可夫模型(HMM)的煤矿安全监测系统。该系统通过构建基于LoRa技术的无线传感网络以及利用带有数据预处理能力的边缘节点,实现对煤炭开采过程中井下作业环境的安全监测数据收集处理。由于监测环境复杂多变且易产生大量数据,网络带宽不足和通信延迟成为急需处理的问题。系统利用边缘节点,应用边缘计算模型,使用HMM进行检测数据处理,再将优化处理后的数据进行上传,从而实现系统低功耗、低延时、高数据传输率的监测效果。

Aiming at the safety problems in coal mine production and mining,designed a coal mine safety monitoring system based on LoRa technology and hidden Markov model(HMM).By constructing a wireless sensor network based on LoRa technology and using edge nodes with data preprocessing capability,the system can collect and process safety monitoring data of underground operation environment during coal mining.Because monitoring environment is complicated and easy to produce large amounts of data,network bandwidth and the communication latency become a problem in urgent need of treatment.The system uses the edge node and edge calculation model,uses the HMM for detecting data processing,then uploads the data after optimization,so as to realize the system monitoring results of low power consumption,low latency and high data transfer rate.