Alexander Gabriel, Babette Tecklenburg, Yann Guillouet, & Frank Sill Torres. (2021). Threat analysis of offshore wind farms by Bayesian networks – a new modeling approach. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 174–185). Blacksburg, VA (USA): Virginia Tech.
Abstract: As a result of the ongoing commitment to climate protection in more and more countries and the corresponding expansion of renewable energies, the importance of renewables for the security of electricity supply is also increasing. Wind energy generated in offshore wind farms already accounts for a significant share of the energy mix and will continue to grow in the future. Therefore, approaches and models for security assessment and protection against threats are also needed for these infrastructures. Due to the special characteristics and geographical location of offshore wind farms, they are confronted with particular challenges. In this context, this contribution outlines how an approach for threat analysis of offshore wind farms is to be developed within the framework of the new research project “ARROWS” of the German Aerospace Center. The authors first explain the structure of offshore wind farms and then present a possible modeling approach using Qualitative function models and Bayesian networks.
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Flávio Horita, João Porto de Albuquerque, Victor Marchezini, & Eduardo M. Mendiondo,. (2016). A qualitative analysis of the early warning decision-making process in disaster management. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Early warning systems are an important means of improving the efficiency of disaster response and preparedness. However, in its analysis of the technological aspects of the infrastructure, the literature has failed to carry out an investigation of early warning process. This paper has sought to take a step toward understanding this issue by carrying out a qualitative analysis of the early warning process in disaster management. This has involved participatory observations and conducting interviews with practitioners from the National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN). The results have shown that this research area is a promising way of increasing efficiency and reducing the response time to warnings. This might be achieved by conducting a process analysis, which could provide evidence and information about bottlenecks or investigate the misuse of information systems or tasks by the players involved.
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Alayne Da Costa Duarte, Marcos R. S. Borges, Jose Orlando Gomes, & De Paulo V. R. Carvalho. (2013). ASC model: A process model for the evaluation of simulated field exercises in the emergency domain. 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. 551–555). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The undefined flow of execution of activities in an evaluation process hampers its implementation. A consistent evaluation process defines interrelated methodological steps that make it easier for the evaluator to lead the process. This article presents a process model for the evaluation of simulated field exercises in the emergency domain, including their sub processes and activities. The proposed model was derived from observations made during real situations of a simulated evacuation exercise of communities in high-risk areas in Rio de Janeiro (Brazil). The motivation came from the finding that the assessment of simulated field exercises is conducted by completing an activity report that does not follow a structural model, an evaluation program or a formal standard. The results of this research show the experts' satisfaction with the application of the model proposed for the development of an evaluation process. The same occurs when comparing to reports currently used by them for this purpose.
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Stefan Sackmann, Marlen Hofmann, & Hans Betke. (2013). Towards the Integration of Place-related Information in Disaster Response Processes. 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. 78–83). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Processes in disaster response management (DRM) and business processes are similar due to their general structure and goals. This encourages us to analyze the suitability of business process management tools and methods in the domain of DRM. One main challenge is the coverage of disaster specific aspects by existing process modeling languages. Since interdependencies between time, activities, and place are critical for process planning, we discuss the necessity for model extension. A special focus lies on the integration of place-related information as well as interdependencies resulting from stationary and mobile activities and resources. The integration of such place-related information is discussed as pre-condition for effective and efficient planning of disaster response processes and their successful management by disaster response workflow management systems.
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Hans-Peter Thamm, Thomas Ludwig, & Christian Reuter. (2013). Design of a process model for unmanned aerial systems (UAS) in emergencies. 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. 478–487). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The electricity network is one of the most important infrastructures in modern industrialized societies. In the case of power outages, the society becomes aware of their dependence on electricity and organizations responsible for recovery work need precise information about the location and the type of the damage, which are usually not available. Unmanned Aerial Systems (UAS), commonly known as drones, are aircrafts without a human pilot on board and may help to collect this information. While many technical approaches for UAS exist, a systematic process model for using UAS in emergencies based on the organizations needs is still missing. Based on the presentation of current types of UAS, approaches of using UAS and workshops with organizations responsible for recovery work (police and fire department, public administration, power supplier) this paper presents a process model for UAS in emergencies, especially power outages, which takes both theoretical findings and human experiences into consideration.
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