|
Audun Stolpe, & Jo Hannay. (2021). On the Adaptive Delegation and Sequencing of Actions. 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. 28–39). Blacksburg, VA (USA): Virginia Tech.
Abstract: Information systems support to crisis response and management relies crucially on presenting actionable information in a manner that supports cognitive processes, and does not overwhelm them. We outline how AI Planning can be used viably to support the \emph{delegation and sequencing} of tasks. The idea is to use standard operating procedures as initial specifications of plans in terms of actors, actions and delegation rules. When expressed in the AI planning language \textit{Answer set Programming} (ASP), machine reasoning can be used in a \textit{pre-incident review} to display relevant delegation and sequencing inherent in a plan. % together with measures of goal achievement. The purpose of this is to uncover weaknesses in the initial plan and to optimize sequencing and delegation to increase the likelihood of achieving goals. Further, adaptive planning can be supported in \textit{during-incident reviews} by updating the current status, upon which ASP will then compute new alternatives. % and corresponding goal achievement measures. At this point, initial goals may no longer be viable and the explicit suggestion of prior sub-optimal goals now worth pursuing can be a game-changer under stress. The conceptual basis we lay out in terms of delegation and sequencing can be readily extended with further planning factors, such as resource requirements, role transfer and goal achievement.
|
|
|
Han Che, & Shuming Liu. (2013). Monitoring data identification for a water distribution system based on data self-recognition approach. 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. 166–170). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Detecting the occurrence of hydraulic accidents or contamination events in the shortest time has always been a significant but difficult task. The simple and efficient way is to identify the sudden changes or outliers hidden in the vast amounts of monitoring data produced minute by minute, which is unpractical for human. A new method, which employs a data self-recognition approach to achieve that automatically, has been proposed in this paper. The autoregressive moving average (ARMA) model was employed in this research to construct the self-recognition model. 56 months monitoring data from Changping water distribution network in Beijing, which was firstly cut into different time-slice series, was used to establish the ARMA model. This provided a prediction confidence interval in order to identify the outliers in the test data series. The results showed a good performance in outlier identification and the accuracy ranges from 90% to 95%.Thus, the ARMA model showed great potential in dealing with monitoring data and achieving the expected performance of data self-recognition technology.
|
|
|
David Wodak, & Kenny Meesters. (2021). How To Improve HO/TO's: An Exploratory Study on The Alignment Between Information, Technology And Crisis teams. 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. 459–470). Blacksburg, VA (USA): Virginia Tech.
Abstract: In the last decade, the number of crises has increased, and have become more complex. Crisis response does not only focus on rescue operations, or separate stages but rather it is an integrated and continuous process. During this continuous process, several handovers take place. A handover is an important, critical but challenging moment during a crisis, due to the organizational factors that influence the handover and the technology used to transfer information. Since these are crucial elements of a Crisis handover, it would indicate that the alignment between these factors could lead to the improvement of Crisis handovers. However, certain barriers resulted in a lack of alignment. An important barrier originates from the organizational processes. These have a lack of focus on which crisis managers are involved in the handover and thus create a lack of alignment between the systems and information used by various crisis teams.
|
|
|
Jutta Hild, Jonathan Ott, Yvonne Fischer, & Christian Glökler. (2010). Markov based decision support for cost-optimal response in security management. 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: In this contribution, we introduce a prototype of a decision support tool for cost-optimal response in security management. The threat situation of a closed infrastructure, exposed to multiple threats, and the corresponding response actions are modeled by a continuous-time Markov decision process (CMDP). Since the CMDP cannot be solved exactly for large infrastructures, the response actions are determined from a heuristic, based on an index rule. The decision support tool's user interface displays the infrastructure's current threat state and proposes the heuristic response actions to the decision maker. In this way, global situation awareness can be enhanced and the decision maker is able to initiate an almost cost-optimal response action in short time.
|
|
|
Marlen Hofmann, Stefan Sackmann, & Hans Betke. (2015). Using Precedence Diagram Method in Process-Oriented Disaster Response Management. 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: When planning and modeling disaster response processes (DRP), the unpredictability of disasters precludes accounting for all eventualities in advance. DRPs are thus typically concretized and adapted after the disaster and during the process?s run-time. Since time is critical and uncertainty typical, planning of DRPs requires methods and tools that support disaster managers in process analysis, process adaptation, and decision making. This contribution presents an approach for identifying concurrent activities that, in needing identical resources at the same time in different locations, are jeopardized by such place-related conflicts. As solution, the approach allows managers to calculate valid execution sequences, eliminate place-related conflicts, and prioritize activities by total execution time. Results are shown to form a novel, reliable basis for contributing to disaster managers? decision support.
|
|
|
Muriel Dufour. (2015). Inter-organizational Resource Coordination between NGOs in emergency responses. 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: Resource coordination between NGOs is crucial to have efficient emergency responses. Information Systems (IS) are a tool facilitating resource transfers, information exchanges, and resource coordination between organizations. They cannot be efficient if they are not adapted to fundamental problems of crisis management and specifically to resource coordination processes. This paper explores the operational aspect of resource transfer processes, the intensity of resource coordination between NGOs, and the characteristics an IS, as a support to those processes, must have to improve the resource coordination. Sixty-five in-depth interviews, documentation, and on-site observations in Chile with 13 NGOs chosen for their diversity allowed identifying different categories of processes. A mixed-transformative approach being used, intensity scores were assigned to processes and global scores were calculated for NGOs, based on their processes. A brief discussion follows on how information systems should be adapted to help these processes to increase coordination intensity.
|
|
|
Zhenyu Yu, Chuanfeng Han, & Ma Ma. (2014). Emergency decision making: A dynamic approach. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 240–244). University Park, PA: The Pennsylvania State University.
Abstract: The dynamic nature of emergency decision making exerts difficulty to decision makers for achieving effective management. In this regard, we suggest a dynamic decision making model based on Markov decision process. Our model copes with the dynamic decision problems quantitatively and computationally, and has powerful expression ability to model the emergency decision problems. We use a wildfire scenario to demonstrate the implementation of the model, as well as the solution to the firefighting problem. The advantages of our model in emergency management domain are discussed and concluded in the last.
|
|