Wireless Sensor Network nodes correlation method in coal mine tunnel based on Bayesian decision

The path selection of active objects in the coal mine tunnel has a strong spatial-temporal correlativity. By analyzing the path choices and reasonably selecting relevance among the WSNs nodes in the coal mine tunnel, it is good to reducing the network energy consumption and improving the efficiency of the network monitoring. This paper analyzes the structural characteristics of the coal mine tunnel based on the minimum error Bayesian decision method and the minimum risk Bayesian decision method. According to the probability of moving objects (to the miners, for example) on the choice between tunnels and crossways, we propose the prediction method of path choose based on Bayesian decision, associated Nodes in tunnel and branch. Experiment validation shows that the Bayesian decision method can effectively link nodes.