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ZHAO Qing,YANG Wei,ZHANG Liya,et al. UAV-assisted energy-efficient data gathering method of mine IoT after disaster[J]. Coal Science and Technology,2023,51(8):228−238. DOI: 10.13199/j.cnki.cst.2022-1151
Citation: ZHAO Qing,YANG Wei,ZHANG Liya,et al. UAV-assisted energy-efficient data gathering method of mine IoT after disaster[J]. Coal Science and Technology,2023,51(8):228−238. DOI: 10.13199/j.cnki.cst.2022-1151

UAV-assisted energy-efficient data gathering method of mine IoT after disaster

  • Mine Internet of Things (MIoT) is of great significance in mine production monitoring and disaster prediction. However, the MIoT is easily affected by mine accidents in data transmission. Accidents often lead to the damage of IoT nodes (IoTN). The surviving IoTNs are limited by low quantity and energy, so it is difficult to complete the task of collecting and transmitting a large number of monitoring data in the roadway. In order to ensure the reliable and energy-efficient data communication of MIoT after disaster, an unmanned aerial vehicle (UAV)-assisted clustered MIoT communication system architecture is established. Based on this, an UAV-assisted data gathering method based on clustering and A* search is proposed. Firstly, the energy consumption of IoTNs and the path length of UAV are considered to construct the objective function. The optimal K is determined by plotting the relationship between the variance distance from the node to the cluster center and the path length of UAV data gathering and different K values. Then the K-means algorithm is used to divide all IoTNs into K clusters. Next, by considering the data gathering energy consumption of UAV and IoTNs, the path planning problem of UAV is established as an optimization problem to minimize the overall energy consumption of MIoT system, and an improved A* search algorithm for UAV data collection path planning is proposed. In this algorithm, the starting point of UAV and all clustering information are input into A * network by using the pointer network. A group of sorted cluster heads output by A * network is the flight path of UAV. Simulation results show that compared with the flat-based UAV data gathering method, the proposed data gathering method significantly reduces the energy consumption of UAV; Compared with two clustered-based UAV data acquisition methods, the proposed method effectively reduces the average and total energy consumption of IoTNs. Therefore, the proposed UAV-assisted data gathering method improves the energy consumption of the MIoT system after disaster, prolongs the network lifetime, and plays an important role in improving the reliability of the MIoT data gathering system after disaster.
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