Real-time wildfire perimeter monitoring provides situational awareness and enhances decision- making during firefighting. Specifically, it helps to assess the current and potential fire behavior and intensity and identify the values at risk and prioritize the protection strategies. Moreover, it allows allocating the firefighting resources and personnel efficiently and effectively and coordi- nate the firefighting operations and communication among different agencies and stakeholders. Lastly, it helps to evaluate the effectiveness and impact of the firefighting actions and adjust them as needed and inform the public and the media about the fire status and the evacuation plans.
This deliverable aims at designing algorithms that will enable a team of flying agents equipped with proper hardware for localization and fire detection to monitor in real-time the wildfire evolution and continuously update the mission control with the fire state. Particular interest is the agents’ effective cooperation to quickly observe the fire initially and then maintain an accurate state of the fire as it becomes larger. Specifically, this report pro- poses a UAV-based system that integrates real-time data collection (using onboard sensors) into a fire propagation model to provide accurate state information on the wildfire perimeter and improves fire prediction. Firstly, a data fusion scheme is devised to employ available his- torical data in combination with real-time measurements to provide updated inputs to the fire propagation model. Then the model is used to predict the future fire perimeter and uses these predictions to guide a team of UAVs to monitor the fire perimeter better. The proposed system is evaluated in extensive simulation experiments, demonstrating its effectiveness for real-time wildfire perimeter propagation tracking.
The details of the proposed approach can be found in the references listed below.
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