Fireguard AI: Advanced Fire Detection and Evacuation Path Guidance System Using IoT and Artificial Intelligence

Abstract: Fire accidents in buildings are a serious threat to human life and infrastructure, especially when the current fire evacuation systems in buildings are lack intelligent and adaptability. So, the solution proposes these system FireGurard AI. Traditional methods of detecting fire are using isolated sensors and alarm mechanism, which often delayed the response and inefficient evacuation. FireGuard AI integrate IOT sensors with deep-learning based computer vision (YOLO V8) for intelligent detection and evacuation planning. A Mobile application is developed to guide the evacuation safely during emergency. The proposed system detects the fire through the CCTV video streams of the building by a YOLO model, then the risk level is evacuated by physical agent which is integrated with IoT sensors and a camera module. The sensor data and visual analysis is to fixed to assess risk level and guide the occupant through safe evacuation path by mobile app and physical actuation like voice assistance, and lights. Using adaptive decision making large experimental evacuation shows that the system improve detection accuracy, reduce false alarm and enhance evacuation efficiency compared to traditional approaches. This proposed solution provides cost effective and intelligent framework for next generation fire system for smart buildings.

Keywords: Fire detection, YOLO V8, Emergency guidance, Path Planning, Evacuation planning, A* path finding algorithm.