Ooms, D. (2023). Civil-Military Interaction: a Case Study to validate a Conceptual Framework. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 501–515). Omaha, USA: University of Nebraska at Omaha.
Abstract: International peace operations in response to complex emergencies require effective interaction between international civil and military participants and local actors. Although these operations frequently occur worldwide, civil-military interaction (CMI) remains problematic. CMI problems are described in the literature at length. However, the knowledge management aspects of these problems have received less attention. The feasibility of technical support solutions for CMI should be investigated using a design science approach. This requires validated models of the structural and behavioral characteristics of the CMI domain. A CMI conceptual framework providing such models has been proposed earlier and should be validated. A case study has been conducted into a Netherlands military CMI organization. This study provides for initial user validation of the models. In follow-on research, the validated conceptual framework is used to structure the investigation of CMI problems, knowledge process deficiencies, and their causal relations. It may subsequently support knowledge engineering-based solution design.
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Pettersson, M. N., Axelsson, J., Svenson, P., & Johansson, A. (2023). Towards a Risk Analysis Method for Systems of Systems: A Case Study on Wildfire Rescue Operations. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 530–545). Omaha, USA: University of Nebraska at Omaha.
Abstract: Crisis management (CM) is facing new challenges due to the increasing complexity of contemporary society. To mitigate a crisis, it is often necessary for a collection of independent systems, people, and organizations to cooperate. These collaborating entities constitute an interconnected socio-technical system of systems (SoS). An important question is how a CM SoS should be constructed to minimize the risk of failure and accurately handle a crisis. SoS pose new challenges in analysing risk during interactions. This paper investigates whether the risk analysis method STAMP (System-Theoretic Accident Model and Processes) is suitable for SoS, using a forest fire rescue operation case study. Results show characteristics of various risk sources and identify some SoS characteristics, such as dynamic structure and latent risks, that are not sufficiently handled in STAMP. The study further contributes to the body of knowledge by presenting potential directions for research on SoS risk assessment methods.
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Kishimoto, M., Osaragi, T., & Chan Yili. (2023). Evaluation of Improvement Projects in Densely Built-Up Area using a Large Earthquake Disaster Simulator: A case study in Kyojima Area, Tokyo. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 546–564). Omaha, USA: University of Nebraska at Omaha.
Abstract: This paper aims to (1) evaluate the disaster mitigation effects of improvement projects in a certain area and (2) provide a basis for strategic planning to promote further improvements. Specifically, we decompose local improvements in the analyzed area into multiple scenarios and examine their effects and issues. First, we describe the “large earthquake disaster simulator,” which estimates property damage and human casualties in a large earthquake. Then, the Kyojima area of Sumida-Ku, Tokyo, is selected as the analyzed area. We decompose the improvement projects implemented during 2006 – 2016 and prepare six scenarios. Finally, a simulation analysis is conducted. We demonstrate that fire spread could be effectively blocked by (1) ensuring sufficient road width and (2) identifying the critical buildings in terms of fire spread mitigation and making them fireproof.
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Hager, F., Reuter-Oppermann, M., Müller, T., & Ottenburger, S. (2023). Towards the Design of a Simulation-based Decision Support System for Mass-Casualty Incidents. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 565–574). Omaha, USA: University of Nebraska at Omaha.
Abstract: In case of a mass-casualty incident, e.g. due to a disaster, a high number of patients need medical care within a short time frame and often, a significant percentage must be transported to a hospital or another suitable care facility. Then, different mass transportation modes (e.g., busses, ships or trains) may be used to quickly transport patients to available medical treatment centres outside of the disaster area. Within the SimPaTrans project, we develop a simulation-based decision support system for locating, sizing and analysing different modes of transport in order to prepare for mass-casualty incidents in Germany. In this paper, we present the outline of the tool as well as a first optimisation use case for transportation patients within the city of Karlsruhe, Germany
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Restel, H. (2023). SimulationOps – Towards a Simulation as-a-Service Platform for Resilient Societies Using a Cross-domain Data Mesh. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 575–585). Omaha, USA: University of Nebraska at Omaha.
Abstract: Cross-domain simulations can be a feasible approach for enhancing disaster resilience as well as promoting resilient societies. This work-in-progress proposes a data-centric process model and software platform architecture called “SimulationOps” aimed at improving cross-domain collaboration between researchers (simulation analysts, simulation modelers) and stakeholders (disaster responders, decision makers) throughout the simulation life cycle for combined simulation artifacts. This way, stakeholders are supported in mitigating disasters, improving overall resilience by gained insights, and improvements in quality and velocity. Applying a four-cycle Design Science Research model to the simulation lifecycle, it combines ideas from modern and agile software engineering practices, simulation-as-a-service approach, and the Data Mesh approach. It combines the technical IT level with the organizational process level to smoothen the workflow for creating, running, and improving cross-domain computer simulation components for both producers as well as consumers of the simulation life cycle.
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Pamukcu, D., W. Zobel, C., & Ge, Y. “G. ”. (2023). Prioritization of disaster-related requests in an IT-enabled public service system. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 586–594). Omaha, USA: University of Nebraska at Omaha.
Abstract: The local government’s continuous support is critical for the well-being of a community during disaster events. E-Government systems that establish and maintain ongoing connections with the community thus play a vital role in supporting crisis response and recovery. Such systems’ ability to adapt to the crisis circumstances and to address emergent needs helps them continue their fundamental functions during disasters. Considering various services might require different amounts and types of resources, prioritization strategies are helpful in determining the processing order of requests. This paper discusses the role of prioritizing services within an e-Government system, to better understand how such a system can be managed to best utilize available resources. The study examines how a well-functioning e-Government system, the Orange County, Florida 311 non-emergency service system, responded to the COVID-19 pandemic and how the changes in service operations requirements can affect service provision, specifically with respect to assigning or re-assigning priority levels.
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Gabriel, A., & Torres, F. S. (2023). Navigating Towards Safe and Secure Offshore Wind Farms: An Indicator Based Approach in the German North and Baltic Sea. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 609–619). Omaha, USA: University of Nebraska at Omaha.
Abstract: Offshore wind farms (OWFs) have become an increasingly relevant form of renewable energy in recent years, with the German North Sea being one of the most active regions in the world. However, the safety and security of OWF have become increasingly important due to the potential threats and risks associated with their growing share in the security of energy supply. This paper aims to present a comprehensive and systematic indicator-based approach to assess the safety and security status of OWFs in the German North Sea. The approach is based on the results of a survey of people working in the offshore industry and draws on the work published by Gabriel et al. (2022). The results of the study suggest that the indicator-based approach is a useful tool for end users to assess the security status of offshore wind farms and can be used for further research and development.
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Toshihiro Osaragi, Koji Ogino, Noriaki Hirokawa, & Takuya Oki. (2022). Severity of Crowding at Evacuation Shelters after a Major Earthquake. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 22–43). Tarbes, France.
Abstract: A number of residents are presumed to evacuate to shelters after a large earthquake. However, the congestion of evacuation shelters has not been enough discussed. In this paper, we propose an evacuation behavior model, which includes sub-models on building damage, water-supply failure, power failure, fire damage, and elevator stall. Using the model estimated using the survey data of the past earthquakes, we discuss the congestion of evacuation shelters under the assumption of Tokyo Bay northern earthquake. Finally, we discuss improvement of water pipes for earthquake resistance to reduce the congestion degree of evacuation shelters, which varies according to regional vulnerability.
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Till Sahlmüller, & Bernd Hellingrath. (2022). Measuring the Resilience of Supply Chain Networks. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 55–67). Tarbes, France.
Abstract: With increasing supply chain complexity, it gets more likely that disruptions ripple through the supply chain network, affecting supply chain performance. As the severity of disruptions depends on the supply chain network structure, it is important to assess the network structure in terms of its resilience. This article presents the results of a literature review (LR) to provide a comprehensive overview of measures used for evaluating the resilience of supply chain networks. The results indicate a wide range of measures applied in literature, focusing on either nodes, paths, or subgraphs of the network. The identified measures are compared regarding the structural characteristics they study and the aspects of supply chain performance they investigate.
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Florent Dubois, Paul Renaud-Goud, & Patricia Stolf. (2022). Dynamic Capacitated Vehicle Routing Problem for Flash Flood Victim’s Relief Operations. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 68–86). Tarbes, France.
Abstract: Flooding relief operations are Dynamic Vehicle Routing Problems (DVRPs). The problem of people evacuation is addressed and formalized in this paper. Characteristics of this DVRP problem applied to the crisis management context and to the requirements of the rescue teams are explained. In this paper, several heuristics are developed and assessed in terms of performance. Two heuristics are presented and adapted to the dynamic problem in a re-optimization approach. An insertion heuristic that inserts demands in the existing plan is also proposed. The evaluation is conducted on various dynamic scenarios with characteristics based on a study case. It reveals better performances for the heuristics with a re-optimization approach.
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Julian Zobel, Ralf Kundel, & Ralf Steinmetz. (2022). CAMON: Aerial-Ground Cooperation System for Disaster Network Detection. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 87–101). Tarbes, France.
Abstract: Information on large-scale disaster areas, like the location of affected civilians, is highly valuable for disaster relief efforts. This information can be collected by an Aerial Monitoring System, using UAVs to detect smart mobile devices carried by civilians. State-of-the-art systems typically rely on a purely passive detection approach. In this paper, we present a cooperative communication system between UAVs and ground-based devices to improve the detection performance of such an Aerial Monitoring System. We provide different approaches for the cooperative information collection and evaluate them in a simulated inner-city scenario. The results highlight the effectiveness of the cooperative system, being able to detect civilian devices in the disaster area faster and more comprehensively than a non-cooperative approach.
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Carole Adam, & Hélène Arduin. (2022). Finding and Explaining Optimal Screening Strategies with Limited Tests during the COVID-19 Epidemics. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 102–115). Tarbes, France.
Abstract: The COVID-19 epidemics has now lasted for 2 years. A vaccine has been found, but other complementary measures are still required, in particular testing, tracing contacts, isolating infected individuals, and respecting sanitary measures (physical distancing, masks). However these measures are not always well accepted and many fake news circulate about the virus or the vaccine. We believe that explaining the mechanisms behind the epidemics and the reasons for the sanitary measures is key to protect the general population from disinformation. To this end, we have developed a simple agent-based epidemic simulator that includes various screening strategies. We show that it can be used to compare the efficiency of various targeting strategies, starting date, and number of daily tests. We also ran an optimisation algorithm that proves that the best strategies consist in testing widely and early. Our simulator is already available to play online, to raise awareness in the general population.
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Ahmed Laatabi, Benoit Gaudou, Chihab Hanachi, Patricia Stolf, & Sébastien Truptil. (2022). Coupling Agent-based Simulation with Optimization to Enhance Population Sheltering. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 116–132). Tarbes, France.
Abstract: Population sheltering is a recurrent problem in crisis management that requires addressing two aspects: evacuating vulnerable people using emergency vehicles and regulating movements of pedestrians and individual vehicles towards shelters. While these aspects have received considerable attention in modeling and simulation literature, very few approaches consider them simultaneously. In this paper, we argue that Agent-Based Modeling and Simulation (ABMS) and Optimization are two complementary approaches that can address the problem of sheltering globally and efficiently and be the basis of coherent frameworks for decision- and policy-making. Optimization can build efficient sheltering plans, and ABMS can explore what-if scenarios and use geospatial data to display results within a realistic environment. To illustrate the benefits of a framework based on this coupling approach, we simulate actual flash flood scenarios using real-world data from the city of Trèbes in South France. Local authorities may use the developed tools to plan and decide on sheltering strategies, notably, when and how to evacuate depending on available time and resources.
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Clara Le Duff, Jean-Philippe Gitto, Julien Jeany, Raphaël Falco, Matthieu Lauras, & Frederick Benaben. (2022). A Physics-based Approach to Evaluate Crisis Impacts on Project Management. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 134–143). Tarbes, France.
Abstract: Project management has become a standard in business. Unfortunately, the projects as well as companies are increasingly subject to major disruptions. In this context, it is of prime importance to have the ability to manage the risks inherent to these projects to best achieve their objectives. The existing approaches of crisis management in the literature no longer seem to be adapted to this new normality. The future of research lies in a more systematic crisis assessment and a better conceptualization of the uncertainty associated with risks. It is necessary to rely on the collection of heterogeneous data in order to maximize the understanding of the project environment and to find a way that best describes and visualizes the influence of crises on the project management processes. This article uses the POD approach and applies it in the context of project management to address these issues.
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Duygu Pamukcu, Christopher Zobel, & Yue Ge. (2022). A Data Envelopment Analysis-based Approach for Managing Performance of Public Service Systems During a Disaster. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 144–153). Tarbes, France.
Abstract: In addition to their normal task of supporting community participation, engagement, and improved information access, information technology-based public service systems are also essential for maintaining critical services and providing effective communication with citizens before, during, and after emergencies. This study focuses on the impacts of disaster events on the operational performance of such service systems and discusses opportunities for managing service efficiency by rearranging and reallocating resources during emergencies. To the best of our knowledge, this is the first attempt to provide a practical method for improving the relative efficiency of public service systems in such a context. We suggest a Data Envelopment Analysis (DEA) approach for quantifying the relative efficiencies associated with service requests from an input-output-based standpoint, and discuss the Orange County (Florida) 311 non-emergency service system, in the context of the COVID-19 pandemic, as an example of how such operational efficiency can be managed during a disruption.
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Alexander Gabriel, Babette Tecklenburg, & Frank Sill Torres. (2022). Threat and Risk Scenarios for Offshore Wind Farms and an Approach to their Assessment. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 162–173). Tarbes, France.
Abstract: Offshore wind farms in the German North and Baltic Seas have a key role to play in the context of the shift towards renewable energy and in securing electricity supplies in the future. At the same time, however, shipping routes in the North and Baltic Seas are among the busiest in the world, wind farms are increasingly being operated unmanned and conflicts increasingly involve a hybrid element. From these constellations and competing interests, various risk and threat scenarios emerge. By means of a survey among experts from offshore wind industry, this paper first captures the subjective assessment of the risk situation in order to subsequently develop an approach for their evaluation. The paper uses Bayesian networks in order to enable a risk assessment also under inclusion of uncertain parameters.
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Ayda Kianmehr, & Duygu Pamukcu. (2022). Analyzing Citizens’ Needs during an Extreme Heat Event, based on 311 Service Requests: A Case Study of the 2021 Heatwave in Vancouver, British Columbia. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 174–182). Tarbes, France.
Abstract: Heat waves are becoming more common and intense with global climate change, which requires deploying resilience strategies of governments to prepare for long-term trends of higher temperatures and carefully plan emergency responses for such extreme heat events. The British Columbia province of Canada is one of the regions severely affected by extreme climatic events in 2021, which resulted in several deaths and put hundreds of thousands of people scrambling for relief. This study examines the public reactions to one of these extreme climatic events, the 2021 Pacific Northwest heatwave, in a non-emergency service request platform to uncover the types of municipal service needs during severe climatic disasters. City of Vancouver 311 system data is used to identify the impact of the heatwave on the frequency and types of service needs and examine the significance of the relationship between climatic conditions and the non-emergency service volumes.
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Julian Zobel, Patrick Lieser, Tobias Meuser, Lars Baumgärtner, Mira Mezini, & Ralf Steinmetz. (2021). Modeling Civilian Mobility in Large-Scale Disasters. 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. 119–132). Blacksburg, VA (USA): Virginia Tech.
Abstract: When disasters destroy critical communication infrastructure, smartphone-based Delay-Tolerant Networks (DTNs) can provide basic communication for civilians. Although field tests have shown the practicability of such systems, real-world experiments are expensive and hardly repeatable. Simulations are therefore required for the design and extensive evaluation of novel DTN protocols, but meaningful assertions require realistic mobility models for civilians. In this paper, trace files from a large-scale disaster field test are analyzed to identify typical human behavior patterns in a disaster area. Based on this, we derive a novel civilian disaster mobility model that incorporates identified behaviors such as group-based movement and clustering around points-of-interests such as hospitals and shelters. We evaluate the impact of mobility on DTN communication performance by comparing our model with other established mobility models as well as the trace file dataset in a simulative evaluation based on the field test scenario. In general, our mobility model leads to a more realistic assessment of DTN communication performance compared to other mobility models.
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Tobias Meuser, Lars Baumgärtner, & Patrick Lieser. (2021). Pandemic Skylines: Digital Twins for More Realism in Epidemic Simulations. 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. 133–145). Blacksburg, VA (USA): Virginia Tech.
Abstract: In the recent months, many measures have been taken by governments to fight the COVID-19 pandemic. Due to the unknown properties of the disease and a lack of experience with handling pandemics, the effectiveness of measures taken was often hard to evaluate the effectiveness of measures, leading to inefficient measures and late execution of efficient measures. Many models have been proposed to evaluate the performance of these measures on the spreading of a pandemic, but these models are commonly vastly simplified and, thus, limited in expressiveness. To extend the expressiveness of the models, we developed a epidemic simulation inside of a flexible and scalable city simulation game to analyse the counter measures to a pandemic in this city and spot common places of infection on a microscopic level. The configurability of our developed epidemic simulation will also be useful for potential future pandemics.
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Usman Anjum, Vladimir Zadorozhny, & Prashant Krishnamurthy. (2021). TBAM: Towards An Agent-Based Model to Enrich Twitter Data. 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. 146–158). Blacksburg, VA (USA): Virginia Tech.
Abstract: Twitter is widely being used by researchers to understand human behavior, e.g. how people behave when an event occurs and how it changes their microblogging pattern. The changing microblogging behavior can have an important application in the form of detecting events. However, the Twitter data that is available has limitations in it has incomplete and noisy information and has irregular samples. In this paper we create a model, calledTwitter Behavior Agent-Based Model (TBAM)to simulate Twitter pattern and behavior using Agent-Based Modeling(ABM). The generated data can be used in place or to complement the real-world data and improve the accuracy of event detection. We confirm the validity of our model by comparing it with real data collected from Twitter
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Xiaoyong Ni, Hong Huang, Wenxuan Dong, Chao Chen, Boni Su, & Anying Chen. (2021). Scenario Prediction and Crisis Management for Rain-induced Waterlogging Based on High-precision Simulation. 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. 159–173). Blacksburg, VA (USA): Virginia Tech.
Abstract: Many cities, especially those in developing countries, are not well prepared for the devastating disaster of exceptional rain-induced waterlogging caused by extreme rainfall. This paper proposes a waterlogging scenario prediction and crisis management method for such kind of extreme rainfall conditions based on high-precision waterlogging simulation. A typical urban region in Beijing, China is selected as the study area in this paper. High-precision and full-scale data in the study area requested for the waterlogging simulation are introduced. The simulation results show that the study area is still vulnerable to extreme rainfall and the subsequent waterlogging. The waterlogging situation is much more severe with the increase of the return period of rainfall. This study offers a good reference for the relevant government departments to make effective policy and take pointed response to the waterlogging problem.
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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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Ivar Svare Holand, Peter Mozelius, & Trond Olav Skevik. (2021). A structured and dynamic model for emergency management exercises. 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. 186–197). Blacksburg, VA (USA): Virginia Tech.
Abstract: Emergencies are management challenges, and emergency exercises that involve multiple collaborating parties is a means towards mastering them. Such exercises are often conducted in a virtual training environment based on complex disaster scenarios. The reported study was carried out using a requirement-focused design approach. The aim was to describe and discuss a relevant design for lean, dynamic, and cost-efficient emergency management exercise systems. Data were gathered from a literature study and analyses of earlier emergency management projects in which the authors had participated. Despite the complexity of many current emergency management exercises, the scenarios usually involve only the response phases and have a linear structure that hinders both didactic aspects and the software structure. The conclusion drawn from the study is that an emergency management exercise model should focus on managing the activities that correspond to alternatives that unfold from a dynamic scenario. Finally, the authors recommend the principles of alternate reality games as a way towards more dynamic and cost-efficient emergency exercise systems.
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Victor A. Bañuls, Andrzej M. Skulimowski, & José Antonio Román Begines. (2021). Disaster Resilience Modeling of Municipal Water Supply Infrastructures in the Context of Atmospheric Threats. 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. 198–207). Blacksburg, VA (USA): Virginia Tech.
Abstract: The resilience of water supply infrastructure (WSI) is of utmost importance as threats to predominantly, although not exclusively, urban WSI may accompany virtually all kinds of natural disasters. In this paper, we present some of the challenges posed by climate change in modeling emergencies in WSIs. Climate change is a global phenomenon that significantly impacts global lifestyle. It is expected that increase in global temperatures causes sea levels to rise, increases the number of extreme weather events such as floods, droughts, and storms while highly impacting WSI. In this respect, the challenge is to be prepared for the unexpended by modeling various complex scenarios. Only with a multidisciplinary approach at the global, regional, national, and local levels, can success be achieved. We discuss some of the specific challenges posed by climate change in modeling emergencies in WSIs with a case study modeled using EMERTIC. EMERTIC is a software based on AI and scenarios, that is aimed at supporting decision making at different stages of the Emergency Management cycle.
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Duygu Pamukcu, Christopher Zobel, & Yue Ge. (2021). Analysis of Orange County, Florida 311 System Service Requests During the COVID-19 Pandemic. 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. 208–217). Blacksburg, VA (USA): Virginia Tech.
Abstract: The Orlando metropolitan area in Florida, where Walt Disney World is located, is intimately familiar with impacts of natural disasters because of the yearly threat of hurricanes in the southeastern United States. One of the tools that has aided them in their efforts to monitor and manage such disasters is their 311 non-emergency call system, through which local residents can issue requests to the municipality for disaster-related information or other services. This paper provides a preliminary examination of the potential for the Orange County 311 system to provide actionable information to them in support of their efforts to manage a different type of disaster: the COVID-19 pandemic. The potential of the system to support the County in this context is illustrated through several preliminary analyses of the complete set of service requests that were registered in the first ten months of 2020.
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