Felix Wex, Guido Schryen, & Dirk Neumann. (2011). Intelligent decision support for centralized coordination during Emergency Response. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Automated coordination is regarded as a novel approaches in Emergency Response Systems (ERS), and especially resource allocation has been understudied in former research. The contribution of this paper is the introduction of two variants of a novel resource allocation mechanism that provide decision support to the centralized Emergency Operations Center (EOC). Two quantitative models are computationally validated using real-time, data-driven, Monte-Carlo simulations promoting reliable propositions of distributed resource allocations and schedules. Various requirements are derived through a literature analysis. Comparative analyses attest that the Monte-Carlo approach outperforms a well-defined benchmark.
|
Felix Wex, Guido Schryen, & Dirk Neumann. (2012). Operational emergency response under informational uncertainty: A fuzzy optimization model for scheduling and allocating rescue units. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Coordination deficiencies have been identified after the March 2011 earthquakes in Japan in terms of scheduling and allocation of resources, with time pressure, resource shortages, and especially informational uncertainty being main challenges. We suggest a decision support model that accounts for these challenges by drawing on fuzzy set theory and fuzzy optimization. Based on requirements from practice and the findings of our literature review, the decision model considers the following premises: incidents and rescue units are spatially distributed, rescue units possess specific capabilities, processing is non-preemptive, and informational uncertainty through linguistic assessments is predominant when on-site units vaguely report about incidents and their attributes, or system reports are not exact. We also suggest a Monte Carlo-based heuristic solution procedure and conduct a computational evaluation of different scenarios. We benchmark the results of our heuristic with results yielded through applying a greedy approach. The results indicate that using our Monte Carlo simulation to solve the decision support model inspired by fuzzy set theory can substantially reduce the overall harm. © 2012 ISCRAM.
|
Connie White, Murray Turoff, & Bartel A. Van De Walle. (2007). A dynamic delphi process utilizing a modified thurstone scaling method: Collaborative judgement in emergency response. 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. 7–15). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In an extreme event or major disaster, very often there are both alternative actions that might be considered and far more requests for actions than can be executed immediately. The relative desirability of each option for action could be a collaborative expression of a significant number of emergency managers and experts trying to manage the most desirable alternatives at any given time, in real time. Delphi characteristics can satisfy these needs given that anyone can vote or change their vote on any two options, and voting and scaling are used to promote a group understanding. Further utilized with Thurstone's Law of Comparative Judgment, a group decision or the range of acceptability a group is willing to consent to, can be calculated and utilized as a means of producing the best decision. A ubiquitous system for expeditious real-time decision making by large virtual teams in emergency response environments is described.
|
Gerhard Wickler, George Beckett, Liangxiu Han, Sung Han Koo, Stephen Potter, Gavin Pringle, et al. (2009). Using simulation for decision support: Lessons learned from FireGrid. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper describes some of the lessons learned from the FireGrid project. It starts with a brief overview of the project. The discussion of the lessons learned that follows is intended for others attempting to develop a similar system, where sensor data is used to steer a super-real time simulation in order to generate predictions that will provide decision support for emergency responders.
|
Adam Widera, Hanns-Alexander Dietrich, Bernd Hellingrath, & Jörg Becker. (2013). Understanding humanitarian supply chains – Developing an integrated process analysis toolkit. 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. 210–219). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: In this paper we present the development of an integrated process analysis toolkit for humanitarian logistics. The toolkit integrates a conceptual and a technological component. Our approach follows a case study-based modeling and design approach. The developed concept was evaluated in two humanitarian organizations. Based on these results we extended and integrated the tool-supported process analysis approach, which is ready to use for the structural and quantitative analysis of humanitarian logistics processes. The toolkit can be applied in humanitarian organizations as a decision support tool for designing, planning and executing their logistics processes. Thus, the application affects the preparedness of humanitarian organizations as well as their response performance. The process analysis toolkit is embedded in an overall research agenda with the objective to provide humanitarian organizations with the capabilities to identify, monitor, and improve their logistics processes respecting the organization specific objectives.
|
Duncan T. Wilson, Glenn I. Hawe, Graham Coates, & Roger S. Crouch. (2012). Estimating the value of casualty health information to optimization-based decision support in response to major incidents. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: In this paper we describe a work-in-progress decision support program designed for use in the response to major incidents in the UK. The proposed program is designed for use in a continuous fashion, where the updating of its model, the search for solutions to the model through an optimization algorithm, and the issuing of these solutions are carried out concurrently. The model facilitates the inclusion of dynamic and uncertain features of emergency response. The potential of such an approach to deliver high-quality response plans through enabling more accurate modeling is evaluated through focusing on the case of casualty health information. Computational experiments show there is significant value in monitoring the dynamic and uncertain health progression of casualties and updating the model accordingly. © 2012 ISCRAM.
|
Rene Windhouwer, Gerdien A. Klunder, & F.M. Sanders. (2005). Decision support system emergency planning, creating evacuation strategies in the event of flooding. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 171–180). Brussels: Royal Flemish Academy of Belgium.
Abstract: The Decision Support System (DSS) Emergency Planning is designed for use in the event of sea or river flooding. It makes accessible all the information related to the decision whether to evacuate an area. An important factor in this decision is the time required for the evacuation. The model used by the DSS Emergency Planning system to estimate the time required employs a strategy that prevents congestion on the road network in the area at risk. The use of the DSS Emergency Planning system during the proactive and prevention phases enables disaster containment organisations to prepare better for a flood situation. Moreover, all relevant information is saved and is therefore available for the post-disaster evaluation. The DSS Emergency Planning system can play a significant role in ensuring that the evacuation of an area at risk goes according to plan. In the future the DSS Emergency Planning system can also be used to evacuate people in the event of a nuclear, natural fire or extreme weather disaster.
|
Yaniv Mordecai, & Boris Kantsepolsky. (2018). Intelligent Utilization of Dashboards in Emergency Management. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1108–1119). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Effective decision-supporting visualization is critical for strategic, tactic, and operational management before and during a large-scale climate or extreme weather emergency. Most emergency management applications traditionally consist of map-based event and object visualization and management, which is necessary for operations, but has small contribution to decision makers. At the same time, analytical models and simulations that usually enable prediction and situation evaluation are often analyst-oriented and detached from the operational command and control system. Nevertheless, emergencies tend to generate unpredictable effects, which may require new decision-support tools in real-time, based on alternative data sources or data streams. In this paper, we advocate the use of dashboards for emergency management, but more importantly, we propose an intelligent mechanism to support effective and efficient utilization of data and information for decision-making via flexible deployment and visualization of data streams and metric displays. We employ this framework in the H2020 beAWARE project that aims to develop and demonstrate an innovative framework for enhanced decision support and management services in extreme weather climate events.
|
Xiang Yao, & Murray Turoff. (2007). Using task structure to improve Collaborative Scenario Creation. 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. 591–594). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper provides a task structure design for collaborative scenario elicitation. Task structure design is part of this effort to design a new Collaborative Scenario Creation (CSC) system. The complexity of the scenario creation process hinders participants, especially novice participants, from prudently designing scenarios. Research in Group Decision Support Systems (GDSS) shows that task structure helps to improve processes and collaborations. To design task structure for collaborative scenario elicitation, this paper invokes the Entity-Relationship data modeling methodology.
|
Xiang Yao, Murray Turoff, & Michael J. Chumer. (2009). Designing a group support system to review and practice emergency plans in virtual teams. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In the 21st century, rapid changes of our society necessitate continuous review and practice of emergency plans. Traditional face-to-face (FtF) interactions to make emergency plans and train responders seem insufficient. The virtual team (VT), a new team form allowing dynamic recruitment of experts from global extent and conduction of teamwork whenever it is needed, provides a more agile solution. This paper introduces a group support system called Collario (Collaborative Scenario) aiming to facilitate effective collaboration in creating and discussing scenarios in VTs and to utilize scenarios as the vehicle to review and practice emergency plans on a continuous basis. This research is still in progress. Three professionals have been involved in system demonstrations and interviews. Although it is still too early to make any conclusions, it is encouraging to know that all the three experts thought Collario easy to use and might be useful for various emergency preparedness purposes.
|
Yikun Liu, Sung Pil Moon, Mark Pfaff, Jill L. Drury, & Gary L. Klein. (2011). Collaborative option awareness for emergency response decision making. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: We have been using exploratory modeling to forecast multiple plausible outcomes for a set of decision options situated in the emergency response domain. Results were displayed as a set of box-plots illustrating outcome frequencies distributed across an evaluative dimension (e.g., cost, score, or utility). Our previous research showed that such displays provide what we termed “option awareness” – an ability to determine robust options that will have good outcomes across the broadest number of plausible futures. This paper describes an investigation into extending this approach to collaborative decision making by providing a visualization of both collaborative and individual decision spaces. We believe that providing such visualizations will be particularly important when each individuals decision space does not account for the synergy that may emerge from collaboration. We describe how providing collaborative decision spaces improves the robustness of joint decisions and engenders high confidence in these decisions.
|
Nan Zhang, Clare Bayley, & Simon French. (2008). Use of web-based group decision support for 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. 55–58). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Web-based group decision support systems (wGDSS) are becoming more common in organizations. In this paper, we provide a review and critique of the literature on wGDSS, raising a number of issues that need addressing. Then we report on a small scale experiment using Groupsystems ThinkTank to manage an issue to do with food safety. We also describe how we propose to use ThinkTank in a crisis situation.
|
Andrea Zielinski, Stuart E. Middleton, Laurissa N. Tokarchuk, & Xinyue Wang. (2013). Social media text mining and network analysis for decision support in natural crisis management. 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. 840–845). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: A core issue in crisis management is to extract from the mass of incoming information what is important for situational awareness during mass emergencies. Based on a case study we develop a prototypical application, TweetComp1, which is integrated into the decision-support component of a Tsunami early warning system and demonstrates the applicability of our approach. This paper describes four novel approaches using focused twitter crawling, trustworthiness analysis, geo-parsing, and multilingual tweet classification in the context of how they could be used for monitoring crises. The validity of our state-of-the art text mining and network analysis technologies will be verified in different experiments based on a human annotated gold standard corpus.
|
Christopher W. Zobel. (2010). Comparative visualization of predicted disaster resilience. 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: The disaster resilience triangle is a simple but effective tool for illustrating the relationship between the initial impact of a disaster event and the subsequent time to recovery. This tool can also be expanded, however, to provide an analytic measure of the level of resilience exhibited by a particular entity in a given disaster situation. We build upon the previous work in this area by developing a new approach for visualizing and analyzing the tradeoffs between the two primary defining characteristics of the disaster resilience triangle. This new approach supports strategic decision making in a disaster planning environment by providing a straightforward means for directly comparing the relative predicted resilience of different critical facilities within an organization, with respect to both location and type of risk.
|