FlarePath: Advanced Vehicle Fire Safety and Monitoring with Rapid Emergency Dispatch Solutions

Vehicle fires pose serious risks, often resulting in severe damage and potential fatalities. Current detection systems are primarily reactive, failing to predict and mitigate fire hazards in advance. This research proposes an integrated solution that combines IoT, machine learning, and cloud computing to enhance vehicle fire safety and emergency response. The system uses IoT-enabled sensors to monitor fire indicators like smoke, temperature, and vibrations. Machine learning algorithms analyze this data for early fire prediction, while real-time fire information and vehicle location are transmitted to the nearest fire department, optimizing emergency response with real-time and historical traffic data. An IoT-based automatic fire extinguisher mechanism is implemented to reduce fire impact immediately upon detection. The methodology involves installing sensors, processing data with machine learning, and relaying it to the cloud for analysis. Alerts inform drivers and owners about fire incidents and nearby extinguishers, improving response times. The proposed solution significantly enhances fire safety, demonstrating high accuracy in fire prediction and severity classification.