Claire Laudy. (2017). Rumors detection on Social Media during Crisis Management. 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. 623–632). Albi, France: Iscram.
Abstract: Social Media monitoring has become a major issue in crisis and emergencies management. Indeed, social media may ease the sharing of information between citizens and Public Safety Organizations, but it also enables the rapid spreading of inaccurate information. As information is now provided and shared by anyone to anyone, information credibility is a major issue. We propose an approach to detect rumor in social media. This paper describes our work on semantic graph based information fusion, enhanced with uncertainty management capabilities. The uncertainty management capability enables managing the dierent level of credibility of actors of an emergency (dierent PSO oÿcers and citizens). Functions for information synthesis, conflicting information detection and information evaluation were developed and test during experimentation campaigns. The synthesis and conflicting information detection functionalities are very welcome by end-users. However, the uncertainty management is a combinatorial approach which remains a limitation for use with large amount of information.
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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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Marinus Maris, & Gregor Pavlin. (2006). Distributed perception networks for crisis management. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 376–381). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Situation assessment in crisis management applications can be supported by automated information fusion systems, such as Distributed Perception Networks. DPNs are self-organizing fusion systems that can infer hidden events through interpretation of huge amounts of heterogeneous and noisy observations. DPNs are a logical layer on top of existing communication, sensing, processing and data storage infrastructure. They can reliably and efficiently process information of various quality obtained from humans and sensors through the existing communication systems, such as mobile phone networks or internet. In addition, modularity of DPNs supports efficient design and maintenance of very complex fusion systems. In this paper, a fully functional prototype of a DPN system is presented that fuses information from gas sensors and human observations. The task of the system is to compute probability values for the hypothesis that a particular gas is present in the environment. It is discussed how such a system could be used for crisis management.
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Vladimir Zadorozhny, Pei-Ju Lee, & Michael Lewis. (2015). Collaborative Information Sensemaking for Multi-Robot Search and Rescue. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: In this paper, we consider novel information sensemaking methods for search and rescue operations that combine principles of information fusion and collective intelligence in scalable solutions. We will elaborate on several approaches that originated in different areas of information integration, sensor data management, and multi-robot urban search and rescue missions.
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