Description

Wildfires are escalating in frequency and severity due to climate change, posing increasing threats to human life, infrastructure,and ecosystems. Traditional wildfire management systems struggle to respond effectively to rapidly evolving fire conditions. This research presents a novel, AI-powered Wildfire Emergency Response and Evacuation Framework that integrates autonomous unmanned aerial vehicles (UAVs, AKA “drones”), multi-sensor data fusion, and machine learning (ML) for real-time fire detection, evacuation planning, and search and rescue (SAR) operations. Central to the system is the Dynamic Wildfire Response Algorithm (DWRA), a hybrid decision-making framework combining AI-driven techniques including reinforcement learning (RL), genetic algorithms (GA), and deep learning that enable adaptive and data-driven response coordination. The system uses infrared (IR) and visible-spectrum cameras, LiDAR, weather sensors, and a data processing technique called edge computing (e.g., NVIDIA Jetson AGX Orin) to provide on-board intelligence and low-latency decision-making without cloud reliance. The combination of these sensors and innovations enables the new framework to respond to wildfires with accuracy and efficiency unseen in traditional management systems. Extensive prototype testing of the framework demonstrated a fivefold improvement in fire detection speed, 28% faster evacuation times, and a 35% increase in SAR efficiency over traditional methods. The results confirm the viability of this framework as a scalable, autonomous solution to wildfire emergencies, with the potential to significantly reduce response time, improve situational awareness, and save lives in high-risk fire zones. Future work will focus on expanding drone swarm capabilities, integrating real-time emergency service communication, and enhancing endurance through solar-powered charging infrastructure. By combining innovative technology with real-time adaptability, this research lays the foundation for a next-generation wildfire response system that is faster, smarter, and better equipped to meet the growing challenges of a world grappling with the effects of climate change.

Publication Date

10-1-2025

Publication Type

Report

Topic

Miscellaneous

Digital Object Identifier

10.31979/mti.2025.2446

MTI Project

2446

Keywords

Wildfire, emergency response, evacuation framework, drones, sensing, artificial intelligence

Disciplines

Emergency and Disaster Management

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