ARTIFICIAL INTELLIGENCE-BASED SAFETY SYSTEMS IN ENGINEERING: A COMPREHENSIVE REVIEW OF TECHNOLOGIES, APPLICATIONS, AND FUTURE PROSPECTS
Keywords:
Artificial Intelligence, Engineering Safety, Machine Learning, Predictive Maintenance, Computer Vision, Industrial IoT, Hazard DetectionAbstract
The rapid integration of Artificial Intelligence (AI) into industrial and engineering safety systems has fundamentally transformed the landscape of occupational health, hazard prevention, and accident mitigation. This paper presents a comprehensive review of AI-based safety systems deployed in engineering environments, examining machine learning, computer vision, natural language processing, and sensor-fusion technologies. We analyze real-world deployment statistics across manufacturing, construction, oil & gas, and nuclear industries, demonstrating that AI-enhanced safety protocols have reduced workplace incidents by 35–67% compared to traditional approaches (Zhang et al., 2023). The paper evaluates key enabling technologies, prominent case studies, ethical considerations, and challenges of AI adoption in safety-critical contexts. Findings indicate that predictive analytics and real-time monitoring constitute the most impactful AI safety contributions, while regulatory gaps and data privacy remain primary barriers to large-scale adoption.
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