A wildfire prevention and control emergency system based on AHP method

Yiting Chen; Fengyi Cao; Yutong Xie

doi:10.1117/12.2635806

6 May 2022 A wildfire prevention and control emergency system based on AHP method

Yiting Chen, Fengyi Cao, Yutong Xie

Proceedings Volume 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022); 1225618 (2022) https://doi.org/10.1117/12.2635806
Event: 2022 International Conference on Electronic Information Engineering, Big Data and Computer Technology, 2022, Sanya, China

Abstract

This paper proposed a Drone Arrangement Model. Firstly, this paper established a drone system consisting of EOCs, frontline personnel, SSA drones and Radio Repeater drones. We first determined the personnel distribution according to the heat map we made. According to the distribution of personnel, we found the location of EOCs using the k-means algorithm, ensuring that EOCs can monitor each group of front-line personnel. For the sake of building communication between personnel and EOCs, we took different radio spreadability into consideration and obtained the distribution of Radio Repeater drones. Since the drones have their maximum flight time and recharge time, we found the best arrangement of SSA drones that can minimize the cost. Finally, due to the complexity of Australia’s terrain, fire scales vary from terrain to terrain, we optimized the locations of hovering VHF/UHF radio-repeater drones and SSA drones. Therefore, we changed the flight range from a two-dimensional flat circle to a three-dimensional sphere. To assess the stability of our model, we analyzed the suitability of our model over the next decade in three ways. The sensitivity analysis shows the strong robustness of our model.

Citation Download Citation

Yiting Chen, Fengyi Cao, and Yutong Xie "A wildfire prevention and control emergency system based on AHP method", Proc. SPIE 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022), 1225618 (6 May 2022); https://doi.org/10.1117/12.2635806

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