Mobile crowd sensing coverage and energy optimization in smart coalmine

Mobile crowd sensing (MCS) is a promising diagram for the environmental information collection based on the smart mobile terminal.Nowadays,vehicles with multiple embedded sensors are increasingly being considered as participants to complete various sensing tasks.In order to better perceive the data in the coalmine environment,the coverage quality and energy consumption of the perception data of sensing terminals were studied based on MCS.A new sensing coverage quality indicator called utility function F(Ω) jointly considering the coverage percentage and coverage density was defined.The selection of vehicles as an optimization problem to improve the coverage quality was formulated,then an improved greedy algorithm-coverage quality optimization (CQO) algorithm was proposed.The proposed algorithm with the real vehicle trajectory dataset was formulated and several factors influencing the coverage quality were studied.The experiment results show that the proposed algorithm achieves a better coverage quality.