Using a Brain-Inspired Decision-Making System to Model a Real-Time Responsive Risk Assessment of the Dynamic Tasks Involved with Hazardous Materials

Risk assessment of the operations utilized in processing products and services always deals with uncertainties complexities. The ever-evolving complex dynamic circumstances make it very difficult to identify analyze potential events affecting workers’ safety health. Our first study was on managing risky situations a environment, transport storage residual hazardous materials high variation operational times. It showed that dynamicity functions has direct relation risk accidents suggested such environments require system decide whether perform each new action suspected condition or not. A practical framework, engaged close variable involved events, is needed provide reliable measures for assessment. Based these measures, this framework would help decisions at right time take preventive actions. support decision-making process by recognizing risk-associated features available information offer continuously updated alternatives appropriate actions prevent unsafe operations. In our second study, we developed brain-inspired real-time configuration environments. That builds knowledge from least most similarities between experienced states determine action(s) rapidly reorient safe condition. This paper aims verify study’s proposed performance simulated environment discussed transportation. We extract information, including effective factors, use model be useful daily management as establishing today’s industrial involve dangerous chemical radioactive products.