A Cognitive Architecture Framework for Critical Situation Awareness Systems

摘要: Goal-oriented human-machine situation-awareness systems focus on the challenges related to perception of elements an environment and their state, within a time-space window, comprehension meaning estimation state in future. Present computer-supported situation awareness provide real-time information fusion from different sources, basic data analysis recognition, presentation corresponding using some augmented reality principles. However, still open research challenge is develop advanced supervisory systems, platforms frameworks that support higher-level cognitive activities, integrate domain specific associated knowledge, learning capabilities decision support. To address these challenges, novel architecture framework presented this paper, which emphasizes role Associated Reality as new layer improve perception, understanding prediction agent. As proof concept, particular application for railways safety shown, uses semantic video infrastructure.