Task Allocation and Traffic Route Optimization in Hybrid Fire-fighting Unmanned Aerial Vehicle Network

Kaixin Lan; Bohao Duan; Shichao Qiu; Yang Xiao; Meng Liu; Haocen Dai

doi:10.54097/hset.v9i.1864

Authors

Kaixin Lan
Bohao Duan
Shichao Qiu
Yang Xiao
Meng Liu
Haocen Dai

DOI:

https://doi.org/10.54097/hset.v9i.1864

Abstract

With the increase of extreme weather conditions in the world, the probability of forest fires is increasing. How the forest fire management decision-making system can monitor and control the fire quickly and effectively is the key of forest fire fighting work. This paper uses SSA drones carrying high-definition and thermal imaging cameras and telemetry sensors in conjunction, as well as Repeater drones used to greatly expand the frontline low-power radio range, to support fire management decision-making systems. At the same time, explore a drone cooperation plan to deal with different fire terrains and different scales of fire conditions. The aim of this paper is to improve the existing fire management decision system in order to quickly respond to the emergency fire. Research object for the Australian state of Victoria on October 1, 2019 to January 7, 2020 wildfires, explore SSA drones and Repeater drones in the application of the forest fire, ensure that fire management decision-making system to provide the optimal number deployment scheme of fire task quickly and efficiently, and achieve the maximum efficiency and economic optimal compatibility.

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