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Franclin Foping, & Ioannis M. Dokas. (2013). A saas-based early warning information fusion system for critical infrastructure safety. 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. 156–165). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Maintaining the critical infrastructures, such as Drinking Water Treatment Plants (DWTP), transportation, power generation and communications systems, in a safe state is a complex problem. The effective collaboration, as well as the collection aggregation and dissemination of early warning information among the stakeholders of the Safety Management System (SMS) responsible for the safety of these critical infrastructures are some of the challenges that need to be addressed. This paper argues that the Software as a Service (SaaS) deployment model can offer new ways of enhancing the fusion of early warning information during the operation phase of critical infrastructures. It presents the requirements, the architecture and a number of features of a working prototype SaaS-based early warning information fusion system for DWTP safety issues in the Republic of Ireland. It is the first time that a SaaSbased working prototype system is reported of providing early warning information fusion services in the literature.
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Jo Erskine Hannay, & Yelte Kikke. (2019). Structured crisis training with mixed reality simulations. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: We argue that current technology for crisis training does not explicitly cater well enough for managing training
objectives and skill building metrics throughout the lifespan of training. We suggest how successful crisis training
may be enabled by interoperating next-generation exercise management tools with mixed-reality simulations. We
propose an architecture consisting of (1) a front-end in which training objectives, essential skills, corresponding
events and metrics can be declared, (2) a back-end consisting of simulations that implement the events and metrics
and (3) a middleware which transfers information between the front-end and back-end to enable semi-automatic
composition of the simulations and performance analysis. The purpose of this architecture is to facilitate learning
through the principles of deliberate practice. We indicate where emerging technologies are necessary to achieve this.
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