  In recent years, the increasing prevalence and intensity of wildfires have
posed significant challenges to emergency response teams. The utilization of
unmanned aerial vehicles (UAVs), commonly known as drones, has shown promise in
aiding wildfire management efforts. This work focuses on the development of an
optimal wildfire escape route planning system specifically designed for drones,
considering dynamic fire and smoke models. First, the location of the source of
the wildfire can be well located by information fusion between UAV and
satellite, and the road conditions in the vicinity of the fire can be assessed
and analyzed using multi-channel remote sensing data. Second, the road network
can be extracted and segmented in real time using UAV vision technology, and
each road in the road network map can be given priority based on the results of
road condition classification. Third, the spread model of dynamic fires
calculates the new location of the fire source based on the fire intensity,
wind speed and direction, and the radius increases as the wildfire spreads.
Smoke is generated around the fire source to create a visual representation of
a burning fire. Finally, based on the improved A* algorithm, which considers
all the above factors, the UAV can quickly plan an escape route based on the
starting and destination locations that avoid the location of the fire source
and the area where it is spreading. By considering dynamic fire and smoke
models, the proposed system enhances the safety and efficiency of drone
operations in wildfire environments.
