Anne-Marie Barthe-Delanoë, & Wenxin Mu. (2020). Towards a Context-Aware Systemic Risk Management Framework for the Crisis Response. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 1122–1129). Blacksburg, VA (USA): Virginia Tech.
Abstract: Crisis response is, as any other collaborative networked organization, challenged by changes and vulnerabilities. Moreover, as a complex system with distributed activities and numerous interdependencies, considering the risk of such an organization at a systemic level, including time and space dimensions, is necessary. Systemic risk management is a topic traditionally studied in the finance area. Even if a few researches now focus on the supply chain management area (a more relatable domain regarding crisis response), there is even fewer literature regarding systemic risk management for the crisis response. Thus, this paper proposes first to define systemic risk related to the case of the crisis response. Then, a framework for context-aware systemic risk management is presented, to support the design as well as the follow-up of the crisis response, meeting one of the challenges of the Sendai Framework for Disaster Risk Reduction.
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Mitchell L. Moss, & Anthony M. Townsend. (2006). Disaster forensics: Leveraging crisis information systems for social science. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 305–312). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: This paper contributes to the literature on information systems in crisis management by providing an overview of emerging technologies for sensing and recording sociological data about disasters. These technologies are transforming our capacity to gather data about what happens during disasters, and our ability to reconstruct the social dynamics of affected communities. Our approach takes a broad review of disaster research literature, current research efforts and new reports from recent disasters, especially Hurricane Katrina and the Indian Ocean Tsunami. We forecast that sensor networks will revolutionize conceptual and empiricial approaches to research in the social sciences, by providing unprecedented volumes of high-quality data on movements, communication and response activities by both formal and informal actors. We conclude with a set of recommendations to designers of crisis management information systems to design systems that can support social science research, and argue for the inclusion of post-disaster social research as a design consideration in such systems.
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Dragos Datcu, & Leon J.M. Rothkrantz. (2007). The use of active appearance model for facial expression recognition in crisis environments. 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. 515–524). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In the past a crisis event was notified by local witnesses that use to make phone calls to the special services. They reported by speech according to their observation on the crisis site. The recent improvements in the area of human computer interfaces make possible the development of context-aware systems for crisis management that support people in escaping a crisis even before external help is available at site. Apart from collecting the people's reports on the crisis, these systems are assumed to automatically extract useful clues during typical human computer interaction sessions. The novelty of the current research resides in the attempt to involve computer vision techniques for performing an automatic evaluation of facial expressions during human-computer interaction sessions with a crisis management system. The current paper details an approach for an automatic facial expression recognition module that may be included in crisis-oriented applications. The algorithm uses Active Appearance Model for facial shape extraction and SVM classifier for Action Units detection and facial expression recognition.
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Ulrich Meissen, & Agnès Voisard. (2008). Increasing the effectiveness of early warning via context-aware alerting. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 431–440). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The effective implementation of early warning is one of the best investments for disaster prevention and mitigation. In the last decade, we have witnessed strong efforts and progress towards better risk detection, monitoring and prediction. However, the best warnings are ineffective if they cannot be distributed in a timely way and targeted to people at risk. With the evolvement of new Information and Communication Technologies, we have new opportunities and face new challenges for improving classical warning processes. Based on our experience and research results from two user-centered hydro-meteorological Early Warning Systems (EWS) we present an approach for context-aware alerting that can increase considerably the effectiveness of warning. Furthermore, we introduce an applied evaluation model for the effectiveness of an EWS.
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Raffaele Bruno, Marco Conti, & Andrea Passarella. (2008). Opportunistic networking overlays for ICT services in crisis management. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 689–701). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: ICT infrastructures are a critical asset in today's Information society. Legacy telecommunication systems easily collapse in the face of disruptions due to security incidents or natural disasters. Hence, there is an urgent demand for new architectures and technologies ensuring a more efficient and dependable support for various security missions, such as disaster relief initiatives, first responder operations, critical infrastructure protection, etc. In this paper we advocate the opportunistic networking paradigm to build a self-organizing overlay ICT infrastructure for supporting dependable crisis management services. Our opportunistic framework to “glues together” surviving parts of the pre-existing infrastructure with networks deployed on-demand and users devices, and supports dependable distribution of coherent, updated, and non-contradictory information distribution. Finally, to show the potential advantages of our solution, we present initial results on the performance of different types of opportunistic infrastructures, by particularly highlighting the gains of context-aware systems.
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