Alexandre Ahmad, Olivier Balet, Jesse Himmelstein, Arjen Boin, Maaike Schaap, Paolo Brivio, et al. (2012). Interactive simulation technology for crisis management and training: The INDIGO project. 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: To face the urgent need to train strategic and operational managers in dealing with complex crises, we are researching and developing an innovative decision support system to be used for crisis management and interactive crisis training. This paper provides an overview of current decision-support systems, simulation software and other technologies specifically designed to serve crisis managers. These findings inform the design of a new interactive simulation technology system, where a 3D Common Operational Picture (COP) is shared between tactile digital whiteboard in the command center and mobile devices in the field. © 2012 ISCRAM.
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Marie Bartels. (2014). Communicating probability: A challenge for decision support systems. 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. 260–264). University Park, PA: The Pennsylvania State University.
Abstract: This paper presents observations made in the course of two interorganizational crisis management exercises that were conducted in order to identify requirements for a decision support system for critical infrastructure operators. It brings into focus how different actors deal with the uncertainty of information that is relevant for other stakeholders and therefore is to be shared with them. It was analyzed how the participants articulated und comprehended assessments on how probable the reliability of a given data or prognosis was. The recipients of the information had to consider it when making decisions concerning their own network. Therefore they had to evaluate its reliability. Different strategies emerged.
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Anne Marie Barthe, Sébastien Truptil, & Frédérick Bénaben. (2014). Agility of crisis response: Gathering and analyzing data through an event-driven platform. 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. 250–254). University Park, PA: The Pennsylvania State University.
Abstract: The goal of this article is to introduce a platform (called Agility Service) that gathers and analyses data coming from both crisis response and crisis field by using the principles of Complex Event Processing. As a crisis situation is an unstable phenomenon (by nature or by effect of the applied response), the crisis response may be irrelevant after a while: lack of resources, arrival of a new stakeholder, unreached objectives, over-crisis, etc. Gathering data, analyze and aggregate it to deduce relevant information concerning the current crisis situation, and making this information available to the crisis cell to support decision making: these are the purposes of the described platform. A use case based on the Fukushima's nuclear accident is developed to illustrate the use of the developed prototype.
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Cornelia Caragea, Nathan McNeese, Anuj Jaiswal, Greg Traylor, Hyun-Woo Kim, Prasenjit Mitra, et al. (2011). Classifying text messages for the haiti earthquake. 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: In case of emergencies (e.g., earthquakes, flooding), rapid responses are needed in order to address victims' requests for help. Social media used around crises involves self-organizing behavior that can produce accurate results, often in advance of official communications. This allows affected population to send tweets or text messages, and hence, make them heard. The ability to classify tweets and text messages automatically, together with the ability to deliver the relevant information to the appropriate personnel are essential for enabling the personnel to timely and efficiently work to address the most urgent needs, and to understand the emergency situation better. In this study, we developed a reusable information technology infrastructure, called Enhanced Messaging for the Emergency Response Sector (EMERSE), which classifies and aggregates tweets and text messages about the Haiti disaster relief so that non-governmental organizations, relief workers, people in Haiti, and their friends and families can easily access them.
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Benny Carlé, Fernand Vermeersch, & Carlos Rojas Palma. (2004). Systems improving communication in case of a nuclear emergency: Two information exchange systems in the Belgian Nuclear Research Center. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 57–62). Brussels: Royal Flemish Academy of Belgium.
Abstract: Creating a 'common view' between all stakeholders on the course of an emergency situation and the possible consequences is a challenge for any crisis management organisation. In the SCKâEUR¢CEN nuclear emergency preparedness research two projects address two different and particular communication or information management challenges. The HINES system aims at creating a common view by using an information system as a communication tool in an on-site nuclear emergency response room. The MODEM project uses XML-technology to stimulate communication between scientific experts from different countries and institutes by facilitating the exchange of information used in decision support models used to assess the impact of a release of radioactive material in the environment. Both systems are implemented in prototype phase and used regularly during exercises. © Proceedings ISCRAM 2004.
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Carole Adam, & Cédric Lauradoux. (2022). A Serious Game for Debating about the Use of Artificial Intelligence during the COVID-19 Pandemic. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 554–563). Tarbes, France.
Abstract: Crises always impose a difficult compromise between safety and liberty, and the COVID-19 pandemic is no different. Governments have enforced various sanitary restrictions to reduce virus spread. With the help of Artificial Intelligence (AI), the scale of surveillance has risen to unprecedented levels. However, these technologies entail many risks, from potential errors or biases, to their extended enforcement beyond the duration of the initial crisis. Citizens should be aware that these technologies are not infallible, and measure the consequences of errors, so as to make informed decisions about what they want to accept, and for how long. To this aim, we have designed a serious game in the form of a municipal debate between citizens of a virtual town. Some first test sessions helped us improve the game design, and provided proof of the interest of this game to trigger debates and raise awareness.
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Emma Carter, & Simon French. (2005). Nuclear emergency management in Europe: A review of approaches to decision making. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 247–259). Brussels: Royal Flemish Academy of Belgium.
Abstract: The need for transparent and consistent decision making in nuclear emergency management across local, regional, national and international levels is well recognised. Several decision support systems have been developed to help achieve this; but, by and large, with little consultation with potential DMs and with limited understanding of the emergency management procedures across Europe and how they differ. This work, part of a European Fifth Framework project EVATECH, considers the application of process modelling to document and compare the emergency management process in four countries. We have observed that the four process models are substantially different in their organizational structure and identified differences in where decisions are made, the management of advice and the communication network style. This papers focus is on the results of the comparison and the implications for the design and use of decision support systems.
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Josey Chacko, Loren P Rees, & Christopher W. Zobel. (2014). Improving resource allocation for disaster operations management in a multi-hazard context. 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. 85–89). University Park, PA: The Pennsylvania State University.
Abstract: The initial impact of a disaster can lead to a variety of associated hazards. By taking a multi-hazard viewpoint with respect to disaster response and recovery, there is an opportunity to allocate limited resources more effectively, particularly in the context of long-term planning for community sustainability. This working paper introduces an approach for extending quantitative resource allocation models to consider multiple interrelated hazards. The discussion is motivated by a literature review of existing models and then focuses on changes necessary to take the multiplicity of hazards into consideration in the context of decision support systems for disaster operations management.
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Madhavi M. Chakrabarty, & David Mendonça. (2005). Design considerations for information systems to support critical infrastructure management. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 13–18). Brussels: Royal Flemish Academy of Belgium.
Abstract: This paper develops a set of design considerations for information systems to support the management of interdependent critical infrastructure systems. Constraints on how these systems are managed are oriented along technical, political and organizational dimensions, though objectives along these dimensions may conflict and thus be difficult to satisfy. This paper harnesses methodologies from software engineering and cognitive science in order to specify opportunities for using information systems to support human-centered management of critical infrastructure systems. The particular focus of this work is on developing information systems to support visualization and visual problem solving. Progress to date is discussed in terms of an ongoing research project which uses as a test-bed data associated with lower Manhattan (New York, USA).
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Albert Y. Chen, Feniosky Peña-Mora, Saumil J. Mehta, Stuart Foltz, Albert P. Plans, Brian R. Brauer, et al. (2010). A GIS approach to equipment allocation for structural stabilization and civilian rescue. 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: Efficient request and deployment of critical resources for urban search and rescue operations is vital to emergency response. This paper presents a RFID (Radio Frequency Identification) supported system for on-site data collection to communicate structural condition, to track search and rescue status, and to request and allocate appropriate resources. The system provides a unified interface for efficient posing, gathering, storing and sharing of building assessment information. Visualization and easy access of such information enables rescuers to response to the disaster with better situational awareness. Resource requests are sent to the GIS resource repository service that enables a visual disaster management environment for resource allocation. Request and deployment of critical resources through this system enables lifesaving efforts, with the appropriate equipment, operator, and materials, become more efficient and effective. System development at the Illinois Fire Service Institute has shown promising results.
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Soudip Roy Chowdhury, Muhammad Imran, Muhammad Rizwan Asghar, Amer-Yahia, S., & Carlos Castillo. (2013). Tweet4act: Using incident-specific profiles for classifying crisis-related messages. 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. 834–839). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: We present Tweet4act, a system to detect and classify crisis-related messages communicated over a microblogging platform. Our system relies on extracting content features from each message. These features and the use of an incident-specific dictionary allow us to determine the period type of an incident that each message belongs to. The period types are: Pre-incident (messages talking about prevention, mitigation, and preparedness), during-incident (messages sent while the incident is taking place), and post-incident (messages related to the response, recovery, and reconstruction). We show that our detection method can effectively identify incident-related messages with high precision and recall, and that our incident-period classification method outperforms standard machine learning classification methods.
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Graham Coates, Glenn I. Hawe, Duncan T. Wilson, & Roger S. Crouch. (2011). Adaptive co-ordinated emergency response to rapidly evolving large-scale unprecedented events (REScUE). 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: This paper presents an overview of ongoing research into the development of an integrated framework aimed at adaptive co-ordination of emergency response to dynamic, fast evolving and novel events on a large-scale. The framework consists of (i) a decision support system, supported by rapid adaptive search methods, to enable the real time development of tailored response plans including emergency responder team composition and task allocation to these teams, and (ii) an agent-based simulation of emergency response to large-scale events occurring in real geographical locations. The aim of this research is to contribute to understanding how better agent-based simulation coupled with decision support can be used to enable the effective co-ordination of emergency response, involving the collective efforts and actions of multiple agencies (ambulance services, fire brigades, police forces and emergency planning units), to rapidly evolving large-scale unprecedented events.
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Kelli de Faria Cordeiro, Maria Luiza M Campos, & Marcos R. S. Borges. (2014). Adaptive integration of information supporting decision making: A case on humanitarian logistic. 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. 225–229). University Park, PA: The Pennsylvania State University.
Abstract: There is an urgent demand for information systems to gather heterogeneous information about needs, donations and warehouse stocks to provide an integrated view for decision making in humanitarian logistics. The dynamic flow of information, due to the unpredicted events, requires adaptive features. The traditional relational data model is not suitable due to its schema rigidity. As an alternative, Graph Data models complemented by semantic representations, like Linked Open Data on the Web, can be used. Based on both, this research proposes an approach for the adaptive integration of information and an associated architecture. An application example is discussed in a real scenario where relief goods are managed through a dynamic and multi-perspective view.
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Simone De Kleermaeker, & Jan Verkade. (2013). A decision support system for effective use of probability forecasts. 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. 290–295). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Often, water management decisions are based on hydrological forecasts, which are affected by inherent uncertainties. It is increasingly common for forecasters to make explicit estimates of these uncertainties. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a more strict separation of responsibilities between forecasters and decision maker can be made. A recent study identified some issues related to the effective use of probability forecasts. These add a dimension to an already multi-dimensional problem, making it increasingly difficult for decision makers to extract relevant information from a forecast. Secondly, while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be fully known, including estimates of flood damage and costs and effect of damage reducing measures. Here, we present suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development is outlined.
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Marnix De Ridder, & Chris Twenhöfel. (2004). The design and implementation of a decision support and information exchange system for nuclear emergency management in the Netherlands. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 33–38). Brussels: Royal Flemish Academy of Belgium.
Abstract: An information system for decision support and information exchange is designed and a prototype has been build for use in the Back Office Radiological Information (BORI) of the EPAn; the Dutch nuclear emergency organisation. System developments are directed at a fast and efficient production of a radiological status report and the improvement of information exchange and communications between the participating institutes of BORI. Special attention has been given to network security and the information infrastructure to manage virtual workplaces. We have chosen for a standard web based system development for the presentation and communication facilities. This is supplemented by a GIS based system for the aggregation of measurement data and model calculations. © Proceedings ISCRAM 2004.
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Duco N. Ferro, Jeroen M. Valk, & Alfons H. Salden. (2007). A robust coalition formation framework for mobile surveillance incident management. 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. 479–488). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Given unexpected incidents on routes of guards that check security objects, like banks, one of the most challenging problems is still how to support improvisation by security personnel in taking decisions to prevent or resolve such incidents. Another as important associated problem is how a security company can naturally take advantage of its existing and novel knowledge about its organizational and ICT infrastructures, and the introduction of a decision support system to help leverage of improvisation by humans. To tackle all this, on the one hand we present a dynamic coalition formation framework that allows the (re)configurations of agents that are associated with joint tasks in situational contexts to be evaluated by appropriate value functions. On the other hand, we present a dynamic scale-space paradigm that allows a security company to distill ranked lists of robust context-dependent reconfigurations at critical scales. We highlight the merits of ASK-ASSIST as a solution to the problem of supporting human improvisation.
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Mauro Falasca, Christopher W. Zobel, & Deborah Cook. (2008). A decision support framework to assess supply chain resilience. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 596–605). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Our research is aimed at developing a quantitative approach for assessing supply chain resilience to disasters, a topic that has been discussed primarily in a qualitative manner in the literature. For this purpose, we propose a simulation-based framework that incorporates concepts of resilience into the process of supply chain design. In this context, resilience is defined as the ability of a supply chain system to reduce the probabilities of disruptions, to reduce the consequences of those disruptions, and to reduce the time to recover normal performance. The decision framework incorporates three determinants of supply chain resilience (density, complexity, and node criticality) and discusses their relationship to the occurrence of disruptions, to the impacts of those disruptions on the performance of a supply chain system and to the time needed for recovery. Different preliminary strategies for evaluating supply chain resilience to disasters are identified, and directions for future research are discussed.
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Gary M. Fetter, & Mauro Falasca. (2011). Establishing the need for decision support in disaster debris disposal. 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: One of the most important and costly aspects of recovery operations is debris collection and disposal. The unique nature of disaster debris and the extreme amounts generated as a result of the disaster event create challenges for decision makers that are not typically encountered during every day solid-waste disposal operations. This work-in-progress research is aimed at identifying the unique aspects of disaster debris disposal and the need for decision support, which addresses these unique aspects, to assist emergency management coordinators with allocating resources during on-going debris cleanup operations. We will present a decision support system framework, discuss aspects of the knowledge base, model base, and user interface, and show how an emergency management coordinator might use the system during ongoing daily operations using real-world data from a 2003 Atlantic hurricane.
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Gary M. Fetter, Mauro Falasca, Christopher W. Zobel, & Terry R. Rakes. (2010). A multi-stage decision model for debris disposal operations. 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: As shown by Hurricane Katrina, disposing of disaster-generated debris can be quite challenging. Extraordinary amounts of debris far exceeding typical annual amounts of solid waste are almost instantaneously deposited across a widespread area. Although the locations and amounts of debris can be easily summarized looking back after recovery activities have been completed, they are uncertain and difficult at best to estimate as debris operations begin to unfold. Further complicating matters is that the capacity of cleanup resources, which is dependent upon available equipment, labor, and subcontractors, can fluctuate during on-going cleanup operations. As a result, debris coordinators often modify initial resource assignments as more accurate debris estimates and more stable resource capacities become known. In this research, we develop a computer-based decision support system that incorporates a multi-stage programming model to assist decision makers with allocating debris cleanup resources immediately following a crisis event and during ongoing operations as debris volumes and resource capacities become known with increasing certainty.
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Firoj Alam, Ferda Ofli, Muhammad Imran, & Michael Aupetit. (2018). A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 553–572). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: People increasingly use microblogging platforms such as Twitter during natural disasters and emergencies. Research studies have revealed the usefulness of the data available on Twitter for several disaster response tasks. However, making sense of social media data is a challenging task due to several reasons such as limitations of available tools to analyze high-volume and high-velocity data streams. This work presents an extensive multidimensional analysis of textual and multimedia content from millions of tweets shared on Twitter during the three disaster events. Specifically, we employ various Artificial Intelligence techniques from Natural Language Processing and Computer Vision fields, which exploit different machine learning algorithms to process the data generated during the disaster events. Our study reveals the distributions of various types of useful information that can inform crisis managers and responders as well as facilitate the development of future automated systems for disaster management.
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Simon French, & Carmen Niculae. (2004). Believe in the model: Mishandle the emergency. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 9–14). Brussels: Royal Flemish Academy of Belgium.
Abstract: During the past quarter century there have been many developments in scientific models and computer codes to help predict the ongoing consequences in the aftermath of many types of emergency: e.g. storms and flooding, chemical and nuclear accident, epidemics such as SARS and terrorist attack. Some of these models relate to the immediate events and can help in managing the emergency; others predict longer term impacts and thus can help shape the strategy for the return to normality. But there are many pitfalls in the way of using these models effectively. Firstly, non-scientists and, sadly, many scientists believe in the models' predictions too much. The inherent uncertainties in the models are underestimated; sometimes almost unacknowledged. This means that initial strategies may need to be revised in ways that unsettle the public, losing their trust in the emergency management process. Secondly, the output from these models form an extremely valuable input to the decision making process; but only one such input. Most emergencies are events that have huge social and economic impacts alongside the health and environmental consequences. While we can model the latter passably well, we are not so good at modelling economic impacts and very poor at modelling social impacts. Too often our political masters promise the best 'science-based' decision making and too late realise that the social and economic impacts need addressing. In this paper, we explore how model predictions should be drawn into emergency management processes in more balanced ways than often has occurred in the past. © Proceedings ISCRAM 2004.
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Mark Gaynor, Reuven Messer, Dan Myung, & Steve Moulton. (2006). Applications for emergency medical services. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 579–591). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Today, despite the obvious need, pre-hospital providers cannot send real-time electronic patient care information from the field to a receiving hospital. This lack of field awareness and inability to plan for the arrival-or anticipate the needs-of seriously ill or injured patients can lead to the misdirection of patients and the loss of valuable time in the early phases of resuscitation. We believe, however, that current technology can address these shortcomings and that is the focus of our research efforts. This paper discusses how several countries, including Israel, Sweden, Britain and the United States, are addressing the need to better triage patients from the field to an appropriate hospital or trauma center. It also introduces a potential solution, called iRevive, which uses emerging technology such as sensors, wireless WAN data transport, web services, artificial intelligence, and mobile devices to meet the dynamic needs of first responders and the hospitals they serve.
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Rianne Gouman, Masja Kempen, & Niek Wijngaards. (2010). Actor-agent team experimentation in the context of incident 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: The collaboration between humans (actors) and artificial entities (agents) can be a potential performance boost. Agents, as complementary artificial intelligent entities, can alleviate actors from certain activities, while enlarging the collective effectiveness. This paper describes our approach for experimentation with actors, agents and their interaction. This approach is based on a principled combination of existing empirical research methods and is illustrated by a small experiment which assesses the performance of a specific actor-agent team in comparison with an actor-only team in an incident management context. The REsearch and Simulation toolKit (RESK) is instrumental for controlled and repeatable experimentation. The indicative findings show that the approach is viable and forms a basis for further data collection and comparative experiments. The approach supports applied actor-agent research to show its (dis)advantages as compared to actor-only solutions.
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Klaus Granica, Thomas Nagler, Markus M. Eisl, Mathias Schardt, & Helmut Rott. (2005). Satellite remote sensing data for an alpine related disaster management GIS. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 221–232). Brussels: Royal Flemish Academy of Belgium.
Abstract: Natural disasters are an age-old problem that occur regularly in alpine regions, posing a major threat to the safety of settlements and transport routes. Within the project “Safety of Alpine Routes – Application of Earth Observation Combined with GIS (Hannibal)”, financed by the Ministry of Transport and Innovation, information relevant for disaster management has been extracted from satellite remote sensing and integrated into a newly developed GIS based Decision Support System (DSS). Some of the required map information were inferred from ERS- or from SPOT5- and QUICKBIRD satellites, others were taken from conventional data sources such as maps or Digital Terrain Models.
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Rego Granlund, & Helena Granlund. (2011). GPS impact on performance, response time and communication – A review of three studies. 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: This paper describes the basic work performance analysis from three research projects with a goal to investigate the impact of a decision support system that presents global positioning system (GPS) information to the decision makers in crisis management organizations. The goal was to compare the performance between teams that had access to GPS information in the command post with teams that had access only to paper maps. The method used was controlled experiments with the C3Fire micro-world. A total of 304 participants, forming 48 teams, participated in the three studies. The participants came from three different groups, university students, municipal crisis management organizations and rescue service personnel. The result shows that the performance and communication change depending on if the teams used GPS support or paper maps. The result also shows that the participants' background and perceived complexity of the task have an impact on the results.
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