AI-Enabled Fire Safety Compliance: Integrating Machine Learning with IoT for Risk Mitigation
Year: 2025
Type: article
Abstract: Fire safety is a crucial concern for industries, commercial spaces, and residential areas. Traditional fire safety systems often rely on reactive measures, which result in delayed responses, that in turn risks human life, increases propensities for property damage, and insurance costs. The integration of the Internet of Things (IoT) into fire safety systems has emerged as a revolutionary solution, enabling real-time monitoring, predictive maintenance, and automated emergency responses. IoT-powered fire detection systems utilize interconnected sensors to monitor heat, smoke, gas leaks, and environmental factors continuously, providing instant alerts to stakeholders. Predictive maintenance, powered by AI and IoT analytics, ensures that fire safety equipment remains operational at all times, reducing system failures and false alarms. Furthermore, IoT-driven smart evacuation systems dynamically guide individuals toward the safest escape routes, significantly improving emergency response. This paper explores the various challenges faced by industries without IoT-based fire safety solutions and demonstrates how IoT is enhancing fire prevention, risk assessment, and compliance management. Case studies from smart cities, industrial plants, and residential areas highlight the real- world impact of IoT-enabled fire safety solutions. Additionally, the paper discusses future trends, including AI-driven fire prediction and the role of automation in minimizing fire hazards and risk management. By leveraging IoT in fire safety, industries and residences can create safer environments, reduce economic losses, be prepared for fire events and improve regulatory compliance.
Author: Pratik Dahule
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408764379