Abstract
This article presents the development and implementation of an advanced intelligent fire safety system This system is designed to enhance public safety by enabling rapid fire detection and streamlined evacuation procedures. The system integrates an Arduino microcontroller with MQ-series gas sensors to monitor environmental conditions in real time. A key innovation is the use of a graph theory-based algorithm to dynamically generate optimal evacuation routes, ensuring rapid and safe occupant egress during emergencies. The article details the system architecture, including sensor placement, data acquisition, and decision-making processes. When critical sensor readings are detected, the system activates the evacuation algorithm, guiding occupants through the safest available paths while avoiding hazardous areas. Additionally, the developed software processes sensor inputs, assesses risk levels, and coordinates emergency responses. The paper includes numerical simulations validating the system's effectiveness in various fire scenarios, demonstrating improvements in evacuation times and safety. Future research directions are discussed, such as integrating machine learning for predictive analytics, expanding IoT connectivity for smart city applications, and enhancing multi-sensor fusion for improved accuracy. This work contributes to the advancement of intelligent fire safety solutions, offering scalable and adaptive protection for modern urban infrastructures.