A fuzzy dual expert system for managing situation awareness in a safety supervisory system

Safety supervisory systems continue to increase in degree of automation and complexity as operators are decreasing. As a result, each operator must be able to comprehend and respond to an ever increasing amount of available risky status and alert information. They generally have no difficulty in performing their tasks physically but they are stressed by the task of understanding what is going on in the situation. So in the last two decades, situation awareness has been recognized as a critical foundation for successful decision making across a broad range of complex and dynamic systems. This paper develops a fuzzy dual expert system based approach to enhance situation awareness. The proposed approach has ability to support the operators' understanding and assessing the situations, and to deal with uncertainties, applying fuzzy risk assessment concepts.