Research on Monitoring and Prewarning System of Accident in the Coal Mine Based on Big Data

Abstract

More and more big data come from sensor nodes. There are many sensor nodes placed in the monitoring and prewarning system of the coal mine in China for the purpose of monitoring the state of the environment. It works every day and forms the coal mine big data. Traditional coal mine monitoring and prewarning systems are mainly based on mine communication cable, but they are difficult to place at coal working face tunnels. We use WSN to replace mine communication cable and build the monitoring and prewarning system. The sensor nodes in WSN are energy limited and the sensor data are complicated so it is very difficult to use these data directly to prewarn the accident. To solve these problems, in this paper, a new data aggregation strategy and fuzzy comprehensive assessment model are proposed. Simulations compared the energy consumption, delay time, cooperation cost, and prewarning time with our previous work. The result shows our method is reasonable.

A Study on Industrial IoT for the Mining Industry: Synthesized Architecture and Open Research Directions

“…Various research efforts tried to solve specific problems in the mining industry by introducing IoT such as gas monitoring system [45] and employee positioning system [46] in the coal mine. Other pieces of work tailors dam monitoring and pre-alarm system in mines [47], tracking of equipment for maintenance [48], improving machine safety [49], accident analysis system [50], oxygen concentration system [51], fleet and personnel management system [52], ventilation monitoring system [53], and underground mine air quality pollutant prediction system [54].…”

Survey of Scientific Programming Techniques for the Management of Data-Intensive Engineering Environments

“…In the case of foundations of scientific programming, the work in [173] reviewing the main foundations of scientific programming techniques and the use of pattern matching techniques in large graphs [174] are examples of improvements and works in the scope of software techniques. Finally, applications in coal mining [175], recommendation engines for car sharing services [176], health risk prediction [177], text classification [178], or information security [179] are domains in which data are continuously being generated representing good candidates to apply scientific programming techniques.…”

Analysis and Research on Mine Safety and Management Methods in the Context of Big Data

“…In the context of big data, mine safety management can be achieved by collecting and analyzing a large amount of data. These data include but are not limited to, geological data, equipment operation data, workers' health status, and historical accident records [3][4][5]. By analyzing these data, the safety condition of mines can be monitored in real-time, and potential safety risks can be predicted so that preventive measures can be taken.…”