Zvonko Grzetic, Nenad Mladineo, & Snjezana Knezic. (2008). Emergency management systems to accommodate ships in distress. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 669–678). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: As a future member of the European Union (EU), Croatia has decided to implement EU Directive 2002/59/EC of the European Parliament and of the Council binding all EU member states to define places of refuge for ships in need of assistance off their coasts, or to develop techniques for providing assistance to such ships. Consequently, the Ministry of the Sea, Tourism, Transport and Development of the Republic of Croatia has initiated a project for developing an effective Decision Support System (DSS) for defining the places of refuge for ships in distress at sea. Such a system would include a model based upon GIS and different operational research models, which would eventually result in establishing an integral DSS. Starting points for analysis are shipping corridors, and 380 potential locations for places of refuge designated in the official navigational pilot book. Multicriteria analysis, with GIS-generated input data, would be used to establish worthiness of a place of refuge for each ship category, taking into account kinds of accident. Tables of available intervention resources would be made, as well as analysis of their availability in respect of response time, and quantitative and qualitative sufficiency.
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Qing Gu, & David Mendonça. (2005). Patterns of group information-seeking in a simulated emergency response environment. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 109–116). Brussels: Royal Flemish Academy of Belgium.
Abstract: Groups in emergency response environment may be confronted with problems that cannot be solved by following predefined procedures. They must therefore engage in a collective search for relevant information, cooperating and collaborating as they move towards the deadline. Information technologies and expertise may help shape group information seeking and determine its effectiveness. By understanding how response personnel search for information in emergencies and extending the findings to determine demands on information systems, we may begin to understand how to support and train for skillful information seeking in emergency situations. Accordingly, this research evaluates the impact of decision support systems and member expertise on group information-seeking behavior in a simulated emergency response environment. The results of the evaluation are then used to identify how information technologies may further support information seeking in emergency response.
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John R. Harrald, Theresa I. Jefferson, Frank Fiedrich, Sebnem Sener, & Clinton Mixted-Freeman. (2007). A first step in decision support tools for humanitarian assistance during catastrophic disasters: Modeling hazard generated needs. 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. 51–56). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The US has not yet developed adequate models for estimating hazard generated needs, the necessary first step for developing useful decision support systems needed to estimate the capability and capacity of the response forces required. Modeling and technology required to support the decisions made by humanitarian relief organizations requires scenario driven catastrophic planning. This paper documents the lack of effective decision support tools and systems for humanitarian aid and describes the current state of models and methods used for determination of hazard generated needs. The paper discusses work performed on a catastrophic earthquake preparedness project. It outlines how the results of this project will be used to advance the modeling and decision support capabilities of federal, state and local disaster planners and emergency responders.
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Geoffrey Hoare, Jeffrey Nield, Tom Belcuore, & Tom Rich. (2008). Information needs and decision support in health and medical disasters. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 778–786). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: During a disaster, health and medical decision makers need accurate, timely information. However, it is seldom readily available to the right decision makers, at the right time. Quite a number of databases currently exist with information about health and medical organizations which decision makers need during a disaster. Some of these databases have functions that facilitate decision-making and communication before, during and after a disaster. In theory, linking several existing databases will supply this information. Also, other functions can be provided in one package for incident management and monitoring of the preparedness capacity of a State's health and medical systems. But, this has not happened yet in Florida. This research assessed the different users needs, defined the information required to make good decisions and is testing a pilot decision support system of linked databases.
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Gesine Hofinger, Robert Zinke, & Laura Künzer. (2011). Psychological requirements for crisis and emergency decision-support systems for public transport control centers. 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: Control center staff is used to working with software applications for e.g. surveillance of production processes, for controlling and timing of industrial logistics, and for recording and filing incidents and actions. Yet, decision-support systems for emergency situations pose additional demands on employees in this domain. This paper reports first findings for psychological requirements for decision support systems in the rise of emergencies as identified in a federal German research project in the domain of public transportation. In control centers both the humans on duty who have to intervene during an emergency, and the technical system which provides decision-alternatives for supporting the action are considered. Based on findings of the project, psychological, technical and organizational requirements identified in interviews, observations, document analysis and additional relevant literature are generalized.
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Flávio E. A. Horita, & João Porto De Albuquerque. (2013). An approach to support decision-making in disaster management based on volunteer geographic information (VGI) and spatial decision support systems (SDSS). 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. 301–306). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The damage caused by recent events in Japan in 2011 and USA in 2012 highlighted the need to adopt measures to increase the resilience of communities against extreme events and disasters. In addition to the conventional and official information that is necessary for adaptation to disasters, recently, common citizens residents in the affected areas also began contributing with voluntary qualified and updated information. In this context, this work-in-progress presents an approach that uses voluntary information – Also known by VGI (Volunteered Geographic Information) – As a data source for Spatial Decision Support Systems (SDSS) in order to assist the decision-making in disaster management. Our approach consists of a framework that integrates voluntary and conventional data, a SDSS and processes and methods for decision-making. As a result, it is expected that this approach will assist official organizations in disaster management by providing mechanisms and information.
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Alicia Cabañas Ibañez, Dirk Schwanenberg, Luis Garrote De Marcos, Miguel Francés Mahamud, & Javier Arbaizar González. (2011). An example of Flood Forecasting and Decision-Support System for water management in Spain. 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: The paper provides an overview of past, present and future development in the program to implement a Flood Forecasting and Decision-Support System (DSS) for the SAIH network in some Spanish basins. These tools represent a significant advance by embedding the decision-making components for management of hydraulic infrastructure into the flood forecasting and flood early warning procedures. The DSS has been implemented based on an open-shell platform for integrating various data sources and different simulation models. So far, it covers the Segura, Jucar, Tajo, Duero and Miño-Sil basins, which represent 42% of Spanish territory. Special attention is paid to the decision-support for the operation of the 66 major reservoirs as a fundamental part of flood management.
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Muhammad Imran, Carlos Castillo, Jesse Lucas, Patrick Meier, & Jakob Rogstadius. (2014). Coordinating human and machine intelligence to classify microblog communications in crises. 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. 712–721). University Park, PA: The Pennsylvania State University.
Abstract: An emerging paradigm for the processing of data streams involves human and machine computation working together, allowing human intelligence to process large-scale data. We apply this approach to the classification of crisis-related messages in microblog streams. We begin by describing the platform AIDR (Artificial Intelligence for Disaster Response), which collects human annotations over time to create and maintain automatic supervised classifiers for social media messages. Next, we study two significant challenges in its design: (1) identifying which elements must be labeled by humans, and (2) determining when to ask for such annotations to be done. The first challenge is selecting the items to be labeled by crowd sourcing workers to maximize the productivity of their work. The second challenge is to schedule the work in order to reliably maintain high classification accuracy over time. We provide and validate answers to these challenges by extensive experimentation on real world datasets.
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Muhammad Imran, Shady Elbassuoni, Carlos Castillo, Fernando Díaz, & Patrick Meier. (2013). Extracting information nuggets from disaster- Related messages in social media. 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. 791–801). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Microblogging sites such as Twitter can play a vital role in spreading information during “natural” or man-made disasters. But the volume and velocity of tweets posted during crises today tend to be extremely high, making it hard for disaster-affected communities and professional emergency responders to process the information in a timely manner. Furthermore, posts tend to vary highly in terms of their subjects and usefulness; from messages that are entirely off-topic or personal in nature, to messages containing critical information that augments situational awareness. Finding actionable information can accelerate disaster response and alleviate both property and human losses. In this paper, we describe automatic methods for extracting information from microblog posts. Specifically, we focus on extracting valuable “information nuggets”, brief, self-contained information items relevant to disaster response. Our methods leverage machine learning methods for classifying posts and information extraction. Our results, validated over one large disaster-related dataset, reveal that a careful design can yield an effective system, paving the way for more sophisticated data analysis and visualization systems.
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Yasir Javed, Tony Norris, & David Johnston. (2010). Design approach to an emergency decision support system for mass evacuation. 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: This paper is directed primarily to investigating the information needs of emergency managers following recognition of a risk of volcanic eruption. These needs include type of information required during the collection, integration, synthesis, presentation, and sharing of information. This will identify and model the processes underpinning the design of an emergency decision support system (EDSS). Exploration of the information needs, flows, and processes involved in emergency decision making can improve the design of EDSS both in terms of their content and the all-important human-system interfaces that determine their usability.The information attributes and flows then lead to the development of a prototype system that can be evaluated to test and refine the concepts.
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George N. Kelly. (2005). Emergency management in Europe – Contribution of euratom research. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 261–267). Brussels: Royal Flemish Academy of Belgium.
Abstract: This paper summarises the contribution of EURATOM research to off-site emergency management in Europe over the past two decades. Effort initially focused on the development of methods and software that could be used to underpin the nature and extent of emergency management arrangements and policy. With time, and partially in response to accidents at TMI and Chernobyl, effort shifted to the development of a comprehensive decision support system that could find broad use in real time across Europe in order to better inform decisions on emergency management. The deployment of the developed system across Europe, largely so far at a pre-operational level, is described together with the opportunities this offers for more coherent response to any accident that may in future affect Europe and for better use of scarce resources, both human and otherwise. Indications are given of where further effort or initiatives should be directed with a view to ensuring that the major research achievements are fully and effectively exploited.
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Ali Khalili-Araghi, Uwe Glässer, Hamed Yaghoubi Shahir, Brian Fisher, & Piper Jackson. (2012). Intelligent decision support for emergency responses. 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: With a coastline touching upon the Pacific and Atlantic Oceans, the Great Lakes and the Arctic Sea, the Canadian MSOCs are faced with a daunting task. They are responsible for both routine duties, including patrolling coastal areas and collecting satellite data, as well as critical missions, such as emergency response and crime intervention. Both kinds of mission require the fusion of data from a variety of sources and the orchestration of myriad heterogeneous resources over great physical distances. They must deal with uncertainty, both in terms of what can be known and also in the outcomes of actions, and must interact with an environment prone to dynamic change. We present the architecture and core mechanisms of a decision support system for marine safety and security operations (Glässer, Jackson, Araghi, When and Shahir, 2010). The goal of this system is to enhance complex command and control tasks by improving situational awareness and automating task assignments. This system concept includes adaptive information fusion techniques integrated with decentralized control mechanisms for dynamic resource configuration management and task execution management under uncertainty. Autonomously operating agents employ collaboration and coordination to collectively form an intelligent decision support system. © 2012 ISCRAM.
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Abdullah Konak. (2014). Improving network connectivity in emergency ad hoc wireless networks. 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. 36–44). University Park, PA: The Pennsylvania State University.
Abstract: Wireless Ad Hoc Networks (MANETs) can to provide first responders and disaster management agencies with a reliable communication network in the event of a large-scale natural disaster that devastates majority of the existing communication infrastructure. Without requiring a fixed infrastructure, MANETs can be quickly deployed after a large-scale natural disaster or a terrorist attack. On the other hand, MANETs have dynamic topologies which could be disconnected because of the mobility of nodes. This paper presents a decentralized approach to maintain the connectivity of a MANET using autonomous, intelligent agents. Concepts from the social network analysis along with flocking algorithms are utilized to guide the deployment decision of agents. Unlike a basic flocking algorithm where all nodes have the same importance, network metrics are used to quantify the relative importance of nodes. Computational results are presented to demonstrate the effect of various local agent behaviors on the global network connectivity.
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Lennart Landsberg, David Ganske, Christopher Munschauer, & Ompe Aimé Mudimu. (2020). Using Existing Data to Support Operational Emergency Response in Germany – Current Use Cases, Opportunities and Challenges. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 406–415). Blacksburg, VA (USA): Virginia Tech.
Abstract: The availability of resources in the fire and ambulance services in Germany is facing a radical change. Demographic and social transition is reducing the availability of volunteer personnel, and increasing traffic congestion in cities is resulting in longer travel times for emergency vehicles. This paper presents the findings of the definition phase of a research project that addresses these changes. It shows the basic idea of how resilience of fire and ambulance services can be improved by analyzing operational data from past incidents using artificial intelligence (AI). The primary objective is the development of a decision support system for control center dispatchers, which ensures optimal use of available resources. As the result of the definition phase, this paper gives an overview of existing data, current as well as future use cases and also highlights risks and challenges that have to be considered.
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Tim A. Majchrzak, Oliver Noack, Herbert Kuchen, Philipp Neuhaus, & Frank Ückert. (2010). Towards a decision support system for the allocation of traumatized patients. 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: We present a decision support system for the allocation of traumatized patients. The assignment of patients to vehicles and hospitals is a task that requires detailed up-to-date information but has to be carried out quickly. We pro-pose to support medical staff with an IT system. We especially encourage such a system to be used in cases of mass incidents as it is very problematic – yet essential – To provide all injured with adequate healthcare as fast as possible. Our proposal is a system based on business rules. In this paper we describe the development project's background as well as the system's requirements and some details of its implementation. Moreover, we explain an exemplary scenario to show strengths of our approach. Besides discussing related work, we draw an overview of future tasks.
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Matthias Max, Sigmund Kluckner, & Susann Jentzsch. (2014). Trainings for crisis information systems in civil protection: A German perspective. 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. 518–527). University Park, PA: The Pennsylvania State University.
Abstract: Much research and technical development has been conducted to make crisis management more efficient, especially regarding crisis information systems used to streamline operations of authorities during a crisis. Experts from the German Red Cross mention that there is a need for the development and improvement of specific training methods and structures for such new crisis information systems in command and control centers. They also say that computer simulations could be a practical possibility to train crisis management and response staff. To substantiate this information, interviews were conducted with key officials in the field of German civil protection: command and control center staff, command and control center software trainers and crisis information system managers. This paper presents a qualitative study in the field of training German response personnel in crisis management information systems. The results are presented in three sections: suitable training strategies and structures, challenges and best practices for the implementation of trainings and using simulation as a training method for crisis information systems. The results contain personal experiences, opinions and known best-practices of the interview partners.
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Michael E. Stiso, Aslak Wegner Eide, Ragnhild Halvorsrud, Erik G. Nilsson, & Jan Håvard Skjetne. (2013). Building a flexible common operational picture to support situation awareness in 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. 220–229). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Decision support systems for emergency management tend to focus on making a lot of data meaningful to particular users via a common operational picture (COP). This paper describes one such system, but one that goes further by making the COP flexible enough to support multiple users. Large crises involve frequent role switching between different actors in a response. Hence, predicting the support needs of a given user of a COP is difficult at best, complicating the design process. The solution described here is to use interactive information overlays to enable different users to fit the COP to their particular SA needs. The design was evaluated in two user workshops and a demonstration. In general, it was well-received, but domain experts cautioned that the tool must be usable not only in large crises but in everyday operations, or else it will not be used.
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Stella Moehrle. (2012). Generic self-learning decision support system for large-scale disasters. 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: Large-scale disasters, particularly failures of critical infrastructures, are exceptional situations which cannot be solved with standard countermeasures. The crises are complex and the decision makers face acute time pressure to respond to the disaster. IT based decision support systems provide potential solutions and assist the decision making process. Many decision support systems in emergency response and management concentrate on one kind of disaster. Moreover, complex structures are modeled and recommendations are made rule-based. This work in progress paper describes the first steps towards the development of a generic and self-learning decision support system. The methodology used is case-based reasoning. The paper concludes with a sample emergency decision process. © 2012 ISCRAM.
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Stella Moehrle. (2013). Modeling of countermeasures for large-scale disasters using high-level petri nets. 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. 284–289). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: In order to support decision-making in large-scale disasters, IT-based decision support systems provide appropriate countermeasures to respond to the event. For the implementation of measures, logical and temporal dependencies have to be considered. Furthermore, factors influencing the choice of measures should be taken into account. This paper presents a generic approach to modeling sequences of countermeasures using Highlevel Petri Nets including information about the influencing factors and endangered objects. Moreover, an approach to combining several nets is proposed, which establish new sequences for recommendation. The research is part of the development of a generic decision support system for large-scale disasters. Consequently, the focus is on modeling in a generic manner and on automatic processing.
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Stella Moehrle. (2014). On the assessment of disaster management strategies. 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. 215–219). University Park, PA: The Pennsylvania State University.
Abstract: Decision support systems can recommend strategies for disaster management, which can be further discussed by decision-makers. To provide rationales for the recommendations, the strategies need to be assessed according to relevant criteria. If several strategies are available, the criteria can be used for ranking the strategies. This paper addresses the issue concerning the choice of suitable criteria from several perspectives. The assessment integrates concepts on robustness, experience with regard to the implementation of a strategy, quantifiable ratios which can be deduced from simulations, and system-specific parameters. Objectives are to facilitate transparency with respect to the assessments, to provide a basis for discussions concerning the strategies, and to preserve adaptability and flexibility to account for the variability of disasters and users' preferences. The assessment should be used for ranking solutions gained from a case-based reasoning system and to reveal contributions of criteria values to the overall assessment.
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Muhammad Imran, Firoj Alam, Umair Qazi, Steve Peterson, & Ferda Ofli. (2020). Rapid Damage Assessment Using Social Media Images by Combining Human and Machine Intelligence. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 761–773). Blacksburg, VA (USA): Virginia Tech.
Abstract: Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to infrastructures such as roads, bridges, and buildings. This work analyzes the usefulness of social media imagery content to perform rapid damage assessment during a real-world disaster. An automatic image processing system, which was activated in collaboration with a volunteer response organization, processed ~280K images to understand the extent of damage caused by the disaster. The system achieved an accuracy of 76% computed based on the feedback received from the domain experts who analyzed ~29K system-processed images during the disaster. An extensive error analysis reveals several insights and challenges faced by the system, which are vital for the research community to advance this line of research.
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Niels Netten, & Maarten Van Someren. (2006). Automated support for dynamic information distribution in incident 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. 230–237). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: For all emergency response personnel involved in crisis situations it is essential to timely acquire all information critical to their task performance. However, in practice errors occur in the distribution of information between these collaborating actors leading to mistakes and subsequently more damage to the situation. In this paper we present a prototype system for dynamic information distribution able to support the information flow between collaborating crisis actors. The system has been evaluated by means of simulated experiments that use data from a real incident scenario. The results indicate that automated support by means of Machine Learning method works well. Especially, when actor work context features are included, then the performance on selecting and distributing relevant information is high. Furthermore, actors acquire relevant information much faster making group communication much more efficient.
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Oduor Erick Nelson Otieno, Anna Gryszkiewicz, Nihal Siriwardanegea, & Fang Chen. (2010). Concept for intelligent integrated system for crisis 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 document, we describe the need for providing a uniform common picture that is missing in several crisis management decision support tools. Through research, we have reviewed some existing crisis management support systems in use and noted key user requirements that these tools are missing. A significant point of this research is to stress the importance of developing a decision support system that would improve the way an ideal support system would collect, analyze and disseminate necessary information to a crisis management decision maker. We also note the importance of ensuring that such a tool presents information to its user over a user friendly interface. The structure thus developed should be a standalone application that could be incorporated into existing platforms (Rinkineva, 2004) such as cell phones, PDAs and laptops.
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Peng Xia, Ji Ruan, Dave Parry, Jian Yu, & Sally Britnell. (2023). Enhancing Triage Training for Mass Casualty Incidents with Virtual Reality and Artificial Intelligence. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 68–76). Palmerston North, New Zealand: Massey Unversity.
Abstract: Mass casualty incidents (MCIs) occur with natural or man-made disasters. Training emergency staff for combating MCIs is essential, but the cost can be high as such incidents rarely occur, and a physical simulation is resource-intensive. Triage is a critical task in dealing with MCIs. In this paper, we propose to use Virtual Reality (VR) and Artificial Intelligence (AI) technologies to build a low-cost, high-efficient system for MCI triage training. Our system captures more comprehensive training data and utilizes state-of-the-art AI evaluation methods.
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Stephen Potter, & Gerhard Wickler. (2008). Model-based query systems for emergency response. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 495–503). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In this paper we describe the approach adopted and experiences gained during a project to develop a general architecture that aims to harness advanced sensor, modelling and Grid technologies to assist emergency responders in tackling emergencies (specifically fire emergencies). Here we focus on the command and control aspects of this architecture, and in particular, on a query-based approach that has been adopted to allow end users to interact with available models of physical and other phenomena. The development of this has provided a number of insights about the use of such models, which along with the approach itself, should be of interest to any considering similar applications.
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