During hot and dry weather periods, the risk of wildfire rises steeply. Wildfires are difficult to bring under control, especially when they become large. Often fire fighters can only assess the situation from their location, which does not provide a complete overview of the fire. Additionally, the fire can become dynamic and moves fast. This can bring fire fighters into a risk situation. Therefore, it’s important to detect wildfires at an early state, fully grasp the situation and continue to monitor it during the firefighting operations.
Currently, manned flights are conducted over vulnerable areas to detect fires in time. However, this is very costly. In addition, it is expected that there will be an increased risk of forest fires in the future due to global warming. As a result, more flights will also be needed to cover endangered areas.
In order to be able to cover this effort in the future and to improve the early detection of fire, an autonomous system for detection is desired. Hence in this project a drone for long-distance flights is to be equipped with a sensor system that can detect wildfire and alert the fire department. Additionally, it should monitor the development of the fire so that the fire department can better assess the situation and fight the fire in a target manner.
Development Team: Lorenz Einberger, Lukas Götzinger, Isabella Hufnagl, Leon Seidel, Jelina Unger, Nadine Waldschmidt
Scrum Master: Misha Sadeghi, Simon Dietz
Partner: Feuerwehr Erlangen, Evolonic