Data fusion in deep mine safety monitor based on Markov optimized unbiased gray system

The natural conditions of the deep mine are especially poor and deployment of wireless sensor networks in it is constrained by limited energy and communication resources, Aiming at this problem, a data fusion algorithm based on unbiased gray Markov prediction is proposed to solve this problem. This algorithm uses the unbiased gray Markov prediction model to predict the future data and set the threshold, If the error of the predicted value is within the threshold range, do not send the data, due to the environment in deep coal mine usually relatively stable, so we can reduce the energy consumption by reducing the upload data by using the forecast data. Simulation results shows that the data transfer rate can be reduced under the same threshold, while reducing the energy consumption and extending the network usage time.