A REVIEW PAPER ON AUTOMATED FIRE DETECTION

Abstract

Automated fire detection and localization systems play a pivotal role in enhancing early response mechanisms and minimizing the devastating impact of fires. This review explores recent advancements in technologies and methodologies related to automated fire detection and localization. The study encompasses a comprehensive analysis of various sensing technologies, including infrared, image processing, and machine learning-based approaches. The effectiveness of these systems in diverse environments, such as industrial facilities, residential spaces, and outdoor areas, is evaluated. The review delves into the challenges faced by existing systems, addressing issues related to false alarms, scalability, and real-time response. Additionally, advancements in the integration of Internet of Things (IoT) and artificial intelligence (AI) techniques for more robust fire detection and localization are discussed. The aim is to provide a thorough understanding of the current state of automated fire detection systems, their limitations, and the potential avenues for future research and development in this critical field.