Rita Kovordanyi, Jelle Pelfrene, & Henrik Eriksson. (2014). Supporting Instructors? Decision Making in Simulator-Based Training for Crisis Management. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings ? 11th International Conference on Information Systems for Crisis Response and Management (pp. 225–234). University Park, PA: The Pennsylvania State University.
Abstract: Simulator-based training is often more information-intensive and mentally overloading―both for the trainees
and for the exercise staff―than a corresponding live exercise would be. In particular, massive amounts of data
are produced from the simulation core, and these data are often too detailed, and too low-level to be of direct use
for the human eye. The present paper describes a decision support system aimed at helping exercise instructors
maintain an overview of how the exercise is progressing and how the trainees are performing. The paper describes our experience with implementing a real-time, low-key decision support system employing complex event processing, with focus on meeting the special technical challenges that are associated with the novel approach of implementing high-end, real-time processing on a low-power, 6-inch, mobile Android platform.
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Rita Kovordanyi, Rudolf Schreiner, Jelle Pelfrene, Johan Jenvald, Henrik Eriksson, Amy Rankin, et al. (2012). Real-time support for exercise managers' situation assessment and decision making. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: 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 field-observation 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 real-time 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. © 2012 ISCRAM.
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