DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES

Artificial intelligence (AI), designed to enable machines to perform tasks requiring human cognition, is widely used across many fields. Expert systems (ESs), a subset of AI, solve complex problems via expert knowledge. This study focuses on mitigating prevalent and complex slip, trip, and fall (STF incidents by developing a program called WaSaEx, based on an AI-supported ES. WaSaEx, designed for offline use by occupational safety specialists, offers risk analysis, cost estimation, and training planning for occupational health and safety (OHS). Developed via Python and CLIPS, WaSaEx is ES-based, distinct from other OHS programs. This study introduces the WaSaEx program and evaluates its capability for risk analysis and preventive measures, specifically for reporting STF risks in storage areas. The program uses an L-type (5x5) matrix method to assess risks based on user responses, providing risk scores and preventive measures for each factor. It also systematically accounts for the interaction of risk factors that may lead to accidents. Consequently, WaSaEx offers a cost-effective, knowledge-based solution to enable swift and accurate risk analysis. This methodology delivers validated preventive measures and substantially reduces residual risks, thus fostering improved safety in storage environments. WaSaEx is pivotal in advancing workplace safety standards through its expert framework.