Intelligent Monitoring System Of Personnel Safety In Coal Mine

The safety of underground coal mine personnel is an important part of coal mine production safety.In the current monitoring systems of underground mines,there is no monitoring system with the core goal of ensuring the safety status of underground personnel.Managers are unable to grasp the safety status of underground personnel in real time and make personnel adjustments based on the physical condition of the underground personnel.The application of IoT technology in the mine environment will improve the manager's ability to sense the mine conditions.The system is based on the Internet of Things technology and deep learning technology to design an intelligent monitoring system for the safety of underground personnel.This paper first introduces and analyzes the current status of human state recognition technology in China,as well as the research status of fog calculation and blockchain application in IoT system at home and abroad.Then this paper analyzes the functional requirements of the intelligent monitoring system for the safety of underground personnel,and designs the overall scheme of the system.The system is divided into edge sensing layer,fog decision layer,cloud service layer and management application layer.The edge sensing layer is responsible for sensing various state information of the underground personnel,and then performing data analysis and processing work in situ through the edge sensing algorithm.The edge sensing algorithm is based on long-short-term memory networks in deep learning techniques.The fog decision layer collects all edge sensing node data in the area,and performs abnormal event tracing and decision-making according to the data.The fog decision layer uses a block-chained network architecture for data interaction.This network architecture ensures that the system has strong stability and damage resistance,so that when the network is partially damaged,the system can still provide its own real-time status information for underground workers.The fog decision algorithm is based on the random forest algorithm design.The cloud service layer is used to collect data of the fog decision layer and the edge sensing layer,and provides the control application layer to display in a graphical manner.The intelligent monitoring system for safety status of coal mine personnel designed in this paper has the characteristics of accurate state recognition,high stability and strong anti-damage capability.It provides an effective solution for managers to grasp the safety status of underground personnel in real time,and provides strong support for coal mine safety.Figure 54 table 14 reference 53...