Wildfire Prediction
Paper Abstract:
This work introduces the novel approach of including active suppression by incorporating artificially intelligent agents to a wildfire propagation environment. By employing AI-driven agents within a simulation environment, this research assesses the efficacy of different containment tactics. The simulation utilizes multiple data layers aiming to replicate realistic fire spread scenarios by taking into account wind, fuel moisture, and fire intensity. Initial findings demonstrate a significant improvement in fire containment through strategic AI interventions. Our work underscores the need for further advancements in this area, including the integration of real-time environmental data and the further exploration of agent-based suppression strategies.