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Scientific Programming
Volume 2018, Article ID 9308742, 10 pages
https://doi.org/10.1155/2018/9308742
Research Article

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

1School of Software, Central South University, Changsha, China
2Hunan Vocational Institute of Safety Technology, Changsha, China
3School of Computer Science and Engineering, Xi’an University of Technology, Xi’an 710048, China

Correspondence should be addressed to Zhigang Chen; nc.ude.usc@gzc

Received 25 October 2017; Accepted 5 December 2017; Published 6 March 2018

Academic Editor: Wenbing Zhao

Copyright © 2018 Xu Xia et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.