Open AccessStudy on Intelligent Perception Internet of Things Apply in Mine Safety
Author(s) -
Xü Liu,
Lin Sun,
Daoyuan Wang,
Jingzhao Li
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1646/1/012146
Subject(s) - perception , artificial neural network , kalman filter , the internet , computer science , process (computing) , node (physics) , filter (signal processing) , safety monitoring , engineering , real time computing , computer security , artificial intelligence , computer vision , world wide web , microbiology and biotechnology , structural engineering , neuroscience , biology , operating system
Due to the complexity, multi-source and heterogeneity of mine safety scene perception information, the mine safety monitoring system has some problems, such as slow perception, communication lag, lack of effective information extraction and intelligent decision-making, a mine safety situation perception self configuration system based on the Internet of things is proposed in this paper, the architecture and perception model of mine safety situation perception system are established, and the embedded neuron is designed mine safety monitoring system based on perceptual node and distributed neural network. The unscented Kalman filter is used to adjust the BP neural network to reconcile and process the multi-sensor parameter information. The simulation results show that the system has good fault tolerance and high precision of intelligent decision-making, which plays an important role in improving mine intelligent level and safety production.