In this project, I designed an integrated drone-based system to support wildfire monitoring and rescue operations. The system uses thermal cameras, RGB imaging, and LiDAR to create accurate 3D maps, while AI models detect fire, smoke, and hotspots with high reliability. By combining these technologies, the drone can provide real-time situational awareness, predict fire spread, and suggest the safest rescue routes. The results show that such a system is realistic with today’s hardware and AI tools, and it can significantly reduce risks for rescue teams during extreme wildfires. However, challenges like limited datasets, smoke interference, flight endurance, and regulatory restrictions still need to be addressed. To improve the system, I recommend expanding multi-modal datasets, using multiple coordinated drones, and working with emergency agencies to test the system in real conditions.