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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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Syed Imran, Franclin Foping, Ioannis M. Dokas, & John Feehan. (2010). Towards domain specific modeling approach in early warning system. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: It is of practical significance and great value to design and develop a novel Early Warning System (EWS), which will be used by the personnel of institutions involved in the drinking water delivery governance model of Ireland. In order to help the users of our EWS in representing and codifying their knowledge on the complex coincidences that may drive Water Treatment Plants (WTP) to failures or to hazardous states we propose in this paper a novel approach of using Domain Specific Modeling (DSM) in the domain of EWS for Water Treatment Plants. The novelty of our DSM approach also lies in providing a standalone open source software application rendering profiling of the water utilities, early warning signals, monitoring mechanisms of signals along with capability of assessing the “tendency” of a WTP towards failure, given a set of observed early warning signals.
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