Design of a smart PLC-based fire safety system using fuzzy logic

Abstract

This project aims to develop a smart fire detection and fire-fighting system to enhance fire safety measures of a three fire zone industrial facility. An intelligent fire detection algorithm based on fuzzy logic is proposed, integrating four sensor inputs (smoke obscuration rate, temperature, flame radiance and carbon monoxide concentration) for accurate fire identification and classification. Additionally, a PLC-based automation of the fire-fighting pumping system of each fire zone is developed aiming to optimize fire suppression resource deployment. The integration of these intelligent systems is achieved via a SCADA system, enabling real-time monitoring, control, and decision support. The fire detection algorithm was implemented using the MATLAB software and rigorously tested with simulations performed with the industry-standard NIST Fire Dynamics Simulator yielding highly promising results which demonstrated and validated the detection algorithm's effectiveness and robust performance. These application results demonstrate the potential of intelligent fire detection to significantly improve fire safety, a minimize damage, and protect lives through accurate, rapid response times, and optimized resource allocation.