Real-time Support for Exercise Managers’ Situation Assessment and Decision Making

Exercise managers and instructors have a particularly challenging task in monitoring and controlling on-going exercises, which may involve multiple response teams and organizations in highly complex and continuously evolving crisis situations. Managers and instructors must handle potentially incomplete and conflicting fieldobservation data and make decisions in real-time in order to control the flow of the exercise and to keep it in line with the training objectives. In simulation-based exercises, managers and instructors have access to a rich set of realtime data, with an increased potential to closely monitor the trainees’ actions, and to keep the exercise on track. To assist exercise managers and instructors, data about the on-going exercise can be filtered, aggregated and refined by real-time decision-support systems. We have developed a model and a prototype decision-support system, using stream-based reasoning to assist exercise managers and instructors in real-time. The approach takes advantage of topic maps for ontological representation and a complex-event processing engine for analyzing the data stream from a virtual-reality simulator for crisis-management training. Aggregated data is presented both on-screen, in Twitter, and in the form of topic maps.