Design of a UAV forest fire monitoring and early warning system based on D2D

With the improvement of the performance and capabilities of unmanned aerial vehicle (UAV) platforms, the issue of establishing direct communication between UAVs and assigning tasks for forest fire monitoring has become a key concern. Furthermore, the task assignment issue involves factors such as the number and location of UAVs and targets, as well as their respective capabilities, adding complexity to the task allocation problem. This article addresses the task assignment problem for forest fire monitoring using a UAV cluster. It conducts modeling and research on task allocation based on Device-to-Device (D2D) communication, refining constraint conditions to better align with real-world application scenarios. The allocation model is solved using ant colony algorithm, taking into account various factors such as UAV performance, target characteristics, and quantity. By considering these multiple factors, a rational assignment plan is obtained, enabling the completion of forest fire monitoring and early warning tasks.