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Johan Jenvald, Michael Morin, Toomas Timpka, & Henrik Eriksson. (2007). Simulation as decision support in pandemic influenza preparedness and response. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 295–304). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Outbreak of a destructive pandemic influenza threatens to disrupt societies worldwide. International agencies and national governments have prepared plans and recommendations, but it is often decision-makers with the local authorities that are responsible for implementing the response. A central issue for these decision makers is what interventions are available and effective for the specific local community. The paper presents a simulator architecture and its relation to a workflow for decision support in influenza preparedness and response. The simulator can simulate pandemic scenarios, using localized community models, in the presence of various interventions to support an evaluation of potential response strategies. The architecture includes a customized modeling tool, separated from the simulation engine, which facilitates swift scenario modification and recalculation. This flexibility is essential both to explore alternative solutions in planning, and to adapt to changing requirements, information, and resources in outbreak response. An example simulation, based on actual population data from a reference city, illustrates the approach.
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Joris Field, Arjan Lemmers, Amy Rankin, & Michael Morin. (2012). Instructor tools for virtual training systems. 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: Crisis management exercises require a lot of preparation and planning to ensure that the training objectives are met. This is often a time consuming and expensive process and can be a major barrier to setting up frequent crisis management training sessions. The introduction of virtual training environments to supplement the live exercises enables the development of tools to support the instructors in their planning, management, observation and analysis of training exercises. This can simplify the planning process, and give instructors control over the configuration of the exercises to tailor them to the needs of individual trainees. In this paper we present a tool that supports instructors in the planning of virtual exercises, and can be used to provide templates for live exercises. This tool has been developed with ongoing feedback from instructors and crisis management personnel and forms part of a crisis management virtual training system. © 2012 ISCRAM.
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Michael Morin, Irène Abi-Zeid, Claude-Guy Quimper, & Oscar Nilo. (2017). Decision Support for Search and Rescue Response Planning. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 973–984). Albi, France: Iscram.
Abstract: Planning, controlling and coordinating search and rescue operations is complex and time is crucial for survivors who must be found quickly. The search planning phase is especially important when the location of the incident is unknown. We propose, implement, solve, and evaluate mathematical models for the multiple rectangular search area problem. The objective is to define optimal or near-optimal feasible search areas for the available search and rescue units that maximize the probability of success. We compare our new model to an existing model on problem instances of realistic size. Our results show that we are able to generate, in a reasonable time, near optimal operationally feasible plans for searches conducted in vast open spaces. In an operational context, this research can increase the chances of finding s urvivors. Ultimately, as our models get implemented in the Canadian Coast Guard search planning tool, this can translate into more lives being saved.
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Michael Morin, Irène Abi-Zeid, Thanh Tung Nguyen, Luc Lamontagne, & Patrick Maupin. (2013). Search and surveillance in emergency situations – A gis-based approach to construct optimal visibility graphs. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 452–457). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: We present a methodology to construct optimal visibility graphs from vector and raster terrain data based on the integration of Geographic Information Systems, computational geometry, and integer linear programming. In an emergency situation, the ability to observe an environment, completely or partially, is crucial when searching an area for survivors, missing persons, intruders or anomalies. We first analyze inter-visibility using computational geometry and GIS functions. Then, we optimize the visibility graphs by choosing vertices in a way to either maximize coverage with a given number of watchers or to minimize the number of watchers needed for full coverage.
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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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