Oussema Ben Amara, Daouda Kamissoko, Frédérick Benaben, & Ygal Fijalkow. (2021). Hardware architecture for the evaluation of BCP robustness indicators through massive data collection and interpretation. 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. 71–78). Blacksburg, VA (USA): Virginia Tech.
Abstract: Recently, the concept of robustness measurement has become clearly important especially with the rise of risky events such as natural disasters and mortal pandemics. In this context, this paper proposes an overview of a hardware architecture for massive data collection in the aim of evaluating robustness indicators. This paper essentially addresses the theoretical and general problems that the scientific research is seeking to address in this area, offers a literature review of what already exists and, based on preliminary diagnosis of what the literature has, presents a new approach and some of the targeted findings with a focus on the leading aspects, having a primary objective of explaining the multiple aspects of this research work.
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Svend-Anjes Pahl, & Thomas Thiel-Clemen. (2013). KIS – A crisis team information system. 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. 632–637). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Widespread crises require the deployment of a crisis team, to coordinate the disaster assistance. Because of their low frequency of occurrence and the extensive assignment of volunteers, often only less practical knowledge in managing widespread crises are available on demand. If such a crisis occurs, the gained knowledge must be quickly shared within the team. Current crisis management systems are designed to manage big amounts of situation facts, crisis teams based their work on. But very often these systems are not able to manage information about the linkage of these facts causing the problems. KIS is the first prototype of a crisis team information system, able to combine an ontology based data model for situation representation with the ability to forecast causal chained and spatially related problems derived on situation facts. KIS is able to store and manage this knowledge so that it can easily be shared with others.
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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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Markus Quaritsch, Robert Kuschnig, Hermann Hellwagner, & Bernard Rinner. (2011). Fast aerial image acquisition and mosaicking for emergency response operations by collaborative UAVs. 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: Small-scale unmanned aerial vehicles (UAVs) have recently gained a lot of interest for various applications such as surveillance, environmental monitoring and emergency response operations. These battery-powered and easy-to-steer aerial robots are equipped with cameras and can promptly acquire aerial images. In this paper we describe our system of multiple UAVs that are able to fly autonomously over an area of interest and generate an overview image of that area. Intuitive and easy user interaction is a key property of our system: The user specifies the area of interest on an electronic map. The flight routes for the UAVs are automatically computed from this specification and the generated overview is presented in a Google-Earth like user interface. We have tested and demonstrated our multi-UAV system on a large fire service drill. Our system provided a high-resolution overview image of the 5.5 ha large test site with regular updates, proved that it is easy to handle, fast to deploy, and useful for the firefighters.
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Jaziar Radianti, Julie Dugdale, Jose J. Gonzalez, & Ole-Christoffer Granmo. (2014). Smartphone sensing platform for emergency management. 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. 379–383). University Park, PA: The Pennsylvania State University.
Abstract: The increasingly sophisticated sensors supported by modern smartphones open up novel research opportunities, such as mobile phone sensing. One of the most challenging of these research areas is context-aware and activity recognition. The Smart Rescue project takes advantage of smartphone sensing, processing and communication capabilities to monitor hazards and track people in a disaster. The goal is to help crisis managers and members of the public in early hazard detection, prediction, and in devising risk-minimizing evacuation plans when disaster strikes. In this paper we suggest a novel smartphone-based communication framework. It uses specific machine learning techniques that intelligently process sensor readings into useful information for the crisis responders. Core to the framework is a content-based publish-subscribe mechanism that allows flexible sharing of sensor data and computation results. We also evaluate a preliminary implementation of the platform, involving a smartphone app that reads and shares mobile phone sensor data for activity recognition.
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Rocco Sergio Palermo, & Antonio De Nicola. (2022). A Simulation Framework for Epidemic Spreading in Semantic Social Networks. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 266–273). Tarbes, France.
Abstract: Epidemic spreading simulation in social networks denotes a set of techniques that allow to assess the temporal evolution and the consequences of a pandemic. They were largely used by governments and International health organizations during the COVID-19 world crisis to decide the appropriate countermeasures to limit the diffusion of the disease. Among them, the existing simulation techniques based on a network model aimed at studying the infectious disease dynamics have a prominent role and are widely adopted. However, even if they leverage the topological structure of a social network, they disregard the intrinsic and individual features of its members. A semantic social network is defined as a structure consisting of interlinking layers, which include a social network layer, to represent people and their relationships and a concept network layer, to represent concepts, their ontological relationships and implicit similarities. Here, we propose a novel epidemic simulation framework that allows to describe a community of people as a semantic social network, to adopt the most commonly used compartmental models for describing epidemic spreading, such as Susceptible-Infected-Susceptible (SIS) or Susceptible-Infected-Removed (SIR), and to enable semantic reasoning to increase the accuracy of the simulation. Finally, we show how to use the framework to simulate the impact of a pandemic in a community where the job of each member is known in advance.
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Leon J.M. Rothkrantz. (2013). Crisis management using multiple camera surveillance systems. 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. 617–626). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: During recent disasters such as tsunami, flooding, hurricanes, nuclear disaster, earthquake people have to leave their living areas for their own safety. But it proves that some people are not informed about the evacuation, or are not willing or able to leave or don't know how to leave the hazardous areas. The topic of the paper is how to adapt current video surveillance systems along highway and streets to semi-automatic surveillance systems. When a suspicious event is detected a human operator in the control room has to be alerted to take appropriate actions. The architecture of the system and main modules are presented in the paper. Different algorithms to detect localize and track people are published by the authors elsewhere but are summarized in the current paper. The system has been tested in a real life environment and the test results are presented in the paper.
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Rouba Iskandar, Julie Dugdale, Elise Beck, & Cécile Cornou. (2021). PEERS: An integrated agent-based framework for simulating pedestrians' earthquake evacuation. 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. 86–96). Blacksburg, VA (USA): Virginia Tech.
Abstract: Traditional seismic risk assessment approaches focus on assessing the damages to the urban fabric and the resultant socio-economic consequences, without adequately incorporating the social component of risk. However, the human behavior is essential for anticipating the impacts of an earthquake, and should be included in quantitative risk assessment studies. This paper proposes an interdisciplinary agent-based modeling framework for simulating pedestrians' evacuation in an urban environment during and in the immediate aftermath of an earthquake. The model is applied to Beirut, Lebanon and integrates geo-spatial, socio-demographic, and quantitative behavioral data corresponding to the study area. Several scenarios are proposed to be explored using this model in order to identify the influence of relevant model parameters. These experiments could contribute to the development of improved of emergency management plans and prevention strategies.
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Krispijn Scholte, & Leon J.M. Rothkrantz. (2014). Personal warning system for vessels under bad weather conditions. 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. 359–368). University Park, PA: The Pennsylvania State University.
Abstract: Many services provide weather forecasts, including severe weather alerts for the marine. It proves that many ships neglect the warnings because they expect to be able to handle the bad weather conditions. In order to identify possible unsafe situations the Coast Guard needs to observe marine vessel traffic 24 hours, 7 days a week. In this paper we propose a system that is able to support the Coast Guard. Ships can be localized and tracked individually using the Automatic Identification System (AIS). We present a system which is able to send a personal alert to ships expected to be in danger now or the near future. Ships will be monitored in the dangerous hours and routed to safe areas in the shortest time. The system is based on AIS data, probabilistic reasoning and expertise from the Coast Guard. A first prototype will be presented for open waters around the Netherlands.
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Axel Schulz, Heiko Paulheim, & Florian Probst. (2012). Crisis information management in the Web 3.0 age. 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: The effectiveness of emergency response largely depends on having a precise, up-to-date situational picture. With the World Wide Web having evolved from a small read-only text collection to a large-scale collection of socially created data accessible both to machines and humans alike, with the advent of social media and ubiquitous mobile applications, new sources of information are available. Currently, that potentially valuable information remains mostly unused by the command staff, mainly because the sheer amount of information cannot be handled efficiently. In this paper, we show an approach for turning massive amounts of unstructured citizen-generated content into relevant information supporting the command staff in making better informed decisions. We leverage Linked Open Data and crowdsourcing for processing data from social media, and we show how the combination of human intelligence in the crowd and automatic approaches for enhancing the situational picture with Linked Open Data will lead to a Web 3.0 approach for more efficient information handling in crisis management. © 2012 ISCRAM.
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Huizhang Shen, & Jidi Zhao. (2010). Decision-making support based on the combination of CBR and logic reasoning. 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 recent years, various crises arise frequently and cause tremendous economic and life losses. Meanwhile, current emergency decision models and decision support systems still need further improvement. This paper first proposes a new emergency decision model based on the combination of a new case retrieval algorithm for Case-Based Reasoning (CBR) and logic reasoning, and then address a sample flood disaster emergency decision process to explain the application of the model in practice.
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Huizhang Shen, Jingwen Hu, Jidi Zhao, & Jing Dong. (2012). Ontology-based modeling of emergency incidents and crisis management. 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 the frequent occurrence of emergency incidents in recent years, developing intelligent and effective decision support systems for emergency response and management is getting crucial to the government and public administration. Prior research has made many efforts in constructing crisis databases over the decades. However, existing emergency management systems built on top of these databases provide limited decision support capabilities and are short of information processing and reasoning. Furthermore, ontology based on logic description and rules has more semantics description capability compared to traditional relational database. Aiming to extend existing studies and considering ontology's reusability, this paper presents an approach to build ontology-based DSSs for crisis response and management. © 2012 ISCRAM.
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Simon Mille, Gerard Casamayor, Jens Grivolla, Alexander Shvets, & Leo Wanner. (2022). Automatic Multilingual Incident Report Generation for Crisis Management. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 299–309). Tarbes, France.
Abstract: Successful and effucient crisis management depends on the availability of all accessible relevant information on the incidents during a crisis. The sources of this information are very often multiple and manifold – in particular in the case of environmental crises such as wild fires, floods, drought, etc. For the staff of the control centres it can be a challenge to follow up on all of them. In this paper, we present work in progress on an automatic multilingual incident report generator that produces summaries of all environmental incidents communicated by citizens or authorities in a given time range for a given region in terms of a text message, an audio, a video or an image and analyzed by dedicated modules into uniform knowledge representation structures.
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Alexander Smirnov, Nikolay Shilov, Tatiana Levashova, & Alexey Kashevnik. (2008). Web-service network for disaster management. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 516–525). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The paper addresses the issue of context-aware operational decision support in emergency situations. A decision support system (DSS) developed for this purpose is implemented as a network of a set of Web-services. The Web-services try to organise a service network according to context. Here the context is proposed to be modelled as a “problem model”. It specifies problems to be solved in a particular kind of emergency situation. Context is produced based on the knowledge extracted from the application domain (application ontology) and formalised by a set of constraints. The purpose of the service network is provision the DSS with contextualised information from diverse information sources and solving problems specified in the context. In the framework of context-aware operational decision support, composition of the application ontology for the disaster management domain from the Semantic Web Ontologies is discussed and a hybrid technology of context-aware operational decision support is presented. The technology is based on ontology management, context management, constraint satisfaction, and Web Services. Application of the ideas above is illustrated by an example of a decision support system for real-time resource coordination and situation awareness for logistics management in fire response operations.
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Alexander Smirnov, Tatiana Levashova, Andrew Krizhanovsky, Nikolay Shilov, & Alexey Kashevnik. (2009). Self-organizing resource network for traffic accident response. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Traffic accidents are a common feature of the modern life. The paper proposes an approach addressing response to traffic accidents happened in a smart environment. The idea behind the approach is to self-organize resources of the environment according to the state of the situation caused by the accident. The resources self-organize a collaborative network that comprises physical devices, software services, organizations, and persons. The purpose of the resources is to undertake joint actions for accident response. The disaster response system intended for operating in smart environments has a service-oriented architecture. Some of Web-services making up the architecture are intended to model the accident situations; others model resource functionalities or bear supporting functions. Web-services that model resource functionalities are aligned against the disaster management ontology. This alignment ensures semantic interoperability of the heterogeneous resources. The alignment operation is supported by a tool that identifies similar concepts in the ontology and Web-service descriptions using a machine-readable dictionary. Response to the traffic accident illustrates main ideas described in the paper.
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Alexander Smirnov, Tatiana Levashova, & Nikolay Shilov. (2010). Ubiquitous computing in emergency: Profile-based situation response. 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: Ubiquitous computing opens new possibilities to various aspects of human activities. The paper proposes an approach to emergency situation response that benefits of the ubiquitous computing. The approach is based on utilizing profiles to facilitate the coordination of the activities of the emergency response operation members. The major idea behind the approach is to represent the operation members together with information sources as a network of services that can be configured via negotiation of participating parties. Such elements as profile structure, information source model and negotiation protocol are described in detail.
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Alexander Smirnov, Tatiana Levashova, & Nikolay Shilov. (2013). Context-based knowledge fusion patterns in decision support system for emergency response. 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. 597–606). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The purpose of this paper is discovery of context-based knowledge fusion patterns. Knowledge fusion is considered as an appearance of new knowledge in consequence of processes ongoing in decision support systems. The knowledge fusion processes are considered within a system intended to support decisions on planning emergency response actions. The knowledge fusion patterns are generalized with regard to preservation of internal structures and autonomies of information and knowledge sources involved in the knowledge fusion and to knowledge fusion results. The found patterns give a general idea of knowledge fusion processes taking place at the operational stage of decision support system functioning, i.e. the stage where context-aware functions of the system come into operation. As a practical application, such patterns can support engineers with making choice of knowledge sources to be used in the systems they design.
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Evan A. Sultanik, & Clayton Fink. (2012). Rapid geotagging and disambiguation of social media text via an indexed gazetteer. 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: Microblogging services like Twitter afford opportunities for real time determination of situation awareness during crises as people report, via their statuses, information about events on the ground. An important component of the information included in a tweet are mentions of place names that may be sites of damage, injuries, or relief efforts. Methods for extracting these place names and determining the actual location being referenced are an essential part of the suite of tools required for automated extraction of situation awareness from tweets. Extracting and disambiguating place name mentions from text have been areas of extensive research. Twitter, however, presents challenges given the 140 character restriction on status and the informal, abbreviated language that are a norm in this communication channel. Named entity recognizers, which are dependent on labeled training data, may not be useful in this medium for extracting location mentions because the typical training domains for these taggers are absent the noise found in Twitter statuses. Additionally, the contextual information that is necessary for disambiguating place names is not always present. In this paper, we demonstrate a new technique, RapidGeo, for extracting and disambiguating place names from a location specific Twitter feed using an unsupervised technique for tagging location mentions and relying on the known geographic context of the feed for disambiguation. Our location tagging technique performs much better than an off-the-shelf named entity recognizer and we achieve reasonable precision in disambiguating extracted place names. We argue that such fast, high precision, unsupervised approaches are needed when important, actionable information is required from noisy data sources such as Twitter. © 2012 ISCRAM.
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Tina Mioch, Reinier Sterkenburg, Tatjana Beuker, & Mark A. Neerincx. (2021). Actionable Situation Awareness: Supporting Team Decisions in Hazardous Situations. 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. 62–70). Blacksburg, VA (USA): Virginia Tech.
Abstract: Situation Awareness (SA) has been recognized and studied as an important requirement for an effective task performance of first responders. The integration of increasingly advanced sensor, network and artificial intelligence technology into the work processes affects the building, maintenance and sharing of SA. Connecting SA to decision support models provides new possibilities for the development of actionable SA (aSA), entailing information that guides the momentary decision-making processes of the concerning actors. In the European ASSISTANCE project, we are developing an aSA module that displays information about gas distributions, its current and predicted future states (e.g., entailing risks of breathing-in of toxic gases), with references to effective decision-making patterns for this situation. The aSA model is continuously updated based on sensor data. This paper gives an overview of this aSA module for chemical hazard prediction and corresponding display, and presents initial team design patterns that will be integrated into this display to support its actionability.
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Gaia Trecarichi, Veronica Rizzi, Lorenzino Vaccari, Maurizio Marchese, & Paolo Besana. (2009). Open Knowledge at work: Exploring centralized and decentralized information gathering in emergency contexts. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Real-world experience teaches us that to manage emergencies, efficient crisis response coordination is crucial. ICT infrastructures are effective in supporting the people involved in such contexts, by supporting effective ways of interaction. They also should provide innovative means of communication and information management. At present, centralized architectures are mostly used for this purpose; however, alternative infrastructures based on the use of distributed information sources, are currently being explored, studied and analyzed. This paper aims at investigating the capability of a novel approach (developed within the European project OpenKnowledge1) to support both centralized and decentralized architectures for information gathering. For this purpose, we developed an agent-based e-Response simulation environment fully integrated with the OpenKnowledge infrastructure and through which existing emergency plans are modelled and simulated. Preliminary results show the OpenKnowledge capability of supporting the two afore-mentioned architectures and, under ideal assumptions, a comparable performance in both cases.
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Felix Wex, Guido Schryen, & Dirk Neumann. (2011). Intelligent decision support for centralized coordination during Emergency Response. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Automated coordination is regarded as a novel approaches in Emergency Response Systems (ERS), and especially resource allocation has been understudied in former research. The contribution of this paper is the introduction of two variants of a novel resource allocation mechanism that provide decision support to the centralized Emergency Operations Center (EOC). Two quantitative models are computationally validated using real-time, data-driven, Monte-Carlo simulations promoting reliable propositions of distributed resource allocations and schedules. Various requirements are derived through a literature analysis. Comparative analyses attest that the Monte-Carlo approach outperforms a well-defined benchmark.
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Felix Wex, Guido Schryen, & Dirk Neumann. (2012). Operational emergency response under informational uncertainty: A fuzzy optimization model for scheduling and allocating rescue units. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Coordination deficiencies have been identified after the March 2011 earthquakes in Japan in terms of scheduling and allocation of resources, with time pressure, resource shortages, and especially informational uncertainty being main challenges. We suggest a decision support model that accounts for these challenges by drawing on fuzzy set theory and fuzzy optimization. Based on requirements from practice and the findings of our literature review, the decision model considers the following premises: incidents and rescue units are spatially distributed, rescue units possess specific capabilities, processing is non-preemptive, and informational uncertainty through linguistic assessments is predominant when on-site units vaguely report about incidents and their attributes, or system reports are not exact. We also suggest a Monte Carlo-based heuristic solution procedure and conduct a computational evaluation of different scenarios. We benchmark the results of our heuristic with results yielded through applying a greedy approach. The results indicate that using our Monte Carlo simulation to solve the decision support model inspired by fuzzy set theory can substantially reduce the overall harm. © 2012 ISCRAM.
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Gerhard Wickler. (2013). Validating procedural knowledge in the open virtual collaboration environment. 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. 607–616). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This paper describes the OpenVCE system, which is an open-source environment that integrates Web 2.0 technology and a 3D virtual world space to support collaborative work, specifically in large-scale emergency response scenarios, where the system has been evaluated. The support is achieved through procedural knowledge that is available to the system. OpenVCE supports the distributed knowledge engineering of procedural knowledge in a semi-formal framework based on a wiki. For the formal aspect it relies on a representation used in AI planning, specifically, Hierarchical Task Networks, which corresponds naturally to the way emergency response procedures are described in existing Standard Operating Procedures. Knowledge engineering is supported by domain analysis that may highlight issues with the representation. The main contribution of this paper lies in a reasonably informal description of the analysis. The procedural knowledge available to OpenVCE can be utilized in the environment through plans generated by a planner and given to the users as intelligent, distributed to-do lists. The system has been evaluated in experiments using emergency response experts, and it was shown that procedural uncertainty could be improved, despite the complex and new technologies involved. Furthermore, the support for knowledge engineering through domain analysis has been evaluated using several domains from the International Planning Competition, and it was possible to bring out some issues with these examples.
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Gerhard Wickler, & Stephen Potter. (2010). Standard Operating Procedures: Collaborative development and distributed use. 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 describes a system that supports the distributed development and deployment of Standard Operating Procedures. The system is based on popular, open-source wiki software for the SOP development, and the I-X task-centric agent framework for deployment. A preliminary evaluation using an SOP for virtual collaboration is described and shows the potential of the approach.
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Gerhard Wickler, George Beckett, Liangxiu Han, Sung Han Koo, Stephen Potter, Gavin Pringle, et al. (2009). Using simulation for decision support: Lessons learned from FireGrid. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper describes some of the lessons learned from the FireGrid project. It starts with a brief overview of the project. The discussion of the lessons learned that follows is intended for others attempting to develop a similar system, where sensor data is used to steer a super-real time simulation in order to generate predictions that will provide decision support for emergency responders.
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