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Author Tina Comes; Claudine Conrado; Michael Hiete; Michiel Kamermans; Gregor Pavlin; Niek Wijngaards pdf  openurl
  Title An intelligent decision support system for decision making under uncertainty in distributed reasoning frameworks Type Conference Article
  Year 2010 Publication ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings Abbreviated Journal ISCRAM 2010  
  Volume Issue Pages  
  Keywords Automation; Civil defense; Decision making; Decision support systems; Disasters; Expert systems; Information systems; Intelligent systems; Multi agent systems; Risk management; Decision making under uncertainty; Distributed decision support systems; Distributed reasonings; Emergency management; Intelligent decision support systems; Multi-criteria decision analysis; Scenario-based; Theoretical framework; Information filtering  
  Abstract This paper presents an intelligent system facilitating better-informed decision making under severe uncertainty as found in emergency management. The construction of decision-relevant scenarios, being coherent and plausible descriptions of a situation and its future development, is used as a rationale for collecting, organizing, filtering and processing information for decision making. The development of scenarios is geared to assessing decision alternatives, thus avoiding time-consuming analysis and processing of irrelevant information. The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (principles and processes) to the problem at hand and the information available. This approach ensures that each decision can be founded on a coherent set of scenarios, which was constructed using the best expertise available within a limited timeframe. Our theoretical framework is demonstrated in a distributed decision support system by orchestrating both automated systems and human experts into workflows tailored to each specific problem.  
  Address Institute for Industrial Production, Karlsruhe Institute of Technology (KIT), Germany; D-CIS Lab / Thales Research and Technology, Netherlands  
  Corporate Author Thesis  
  Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Seattle, WA Editor S. French, B. Tomaszewski, C. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN Medium  
  Track Intelligent Systems Expedition Conference 7th International ISCRAM Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 406  
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Author Fahem Kebair; Frédéric Serin pdf  isbn
openurl 
  Title Towards an intelligent system for risk prevention and emergency management Type Conference Article
  Year 2008 Publication Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2008  
  Volume Issue Pages 526-535  
  Keywords Civil defense; Decision support systems; Disasters; Information systems; Intelligent systems; Multi agent systems; Ontology; Semantics; Agent-based architecture; Dynamic environments; Emergency management; Emergency management systems; Emergency planners; Risk prevention; Semantic features; Risk management  
  Abstract Making a decision in a changeable and dynamic environment is an arduous task owing to the lack of information, their uncertainties and the unawareness of planners about the future evolution of incidents. The use of a decision support system is an efficient solution for this issue. Such a system can help emergency planners and responders to detect possible emergencies, as well as to suggest and evaluate possible courses of action to deal with the emergency. We are interested in our work to the modelling of a monitoring preventive and emergency management system, wherein we stress the generic aspect. In this paper we propose an agent-based architecture of this system and we describe a first step of our approach which is the modeling of information and their representation using a multiagent system.  
  Address Laboratoire d'Informatique de Traitement de l'Information et des Systèmes, University of le Havre, France  
  Corporate Author Thesis  
  Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Washington, DC Editor F. Fiedrich, B. Van de Walle  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9780615206974 Medium  
  Track Intelligent Systems for Crisis and Disaster Management Expedition Conference 5th International ISCRAM Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 646  
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Author Mohd Khairul Azmi Hassan; Yun-Heh Chen-Burger pdf  isbn
openurl 
  Title Communication and Tracking Ontology Development for Civilians Earthquake Disaster Assistance Type Conference Article
  Year 2016 Publication ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2016  
  Volume Issue Pages  
  Keywords Ontology; Mobile Application; Semantic Web; Linked Data; Communication; Earthquake; Natural Disaster; Disaster Relief; Intelligent Systems; Decision Support Systems  
  Abstract One of the most important components of recovery and speedy response during and immediately after an earthquake disaster is a communication and tracking which possibly capable of discovering affected peoples and connects them with their families, friends, and communities with first responders and/or to support computational systems. With the capabilities of current mobile technologies, we believed that it can be a smart earthquake disaster tools aid to help people in this situation. Ontologies are becoming crucial parts to facilitate an effective communication and coordination across different parties and domains in providing assistance during earthquake disasters, especially where affected locations are remote, affected population is large and centralized coordination is poor. Several existing competing methodologies give guidelines as how ontology may be built, there are no single right ways of building an ontology and no standard of Disaster Relief Ontology exist, although separated related ontologies may be combined to create an initial version. This article discusses the on-going development of an ontology for a Communication and Tracking System (CTS), based on existing related ontologies, that is aimed to be used by mobile phone applications to support earthquake disaster relief at the real-time.  
  Address  
  Corporate Author Thesis  
  Publisher Federal University of Rio de Janeiro Place of Publication Rio de Janeiro, Brasil Editor A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3391 ISBN 978-84-608-7984-12 Medium  
  Track Intelligent Decision Support in the Networked Society Expedition Conference 13th International Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 1330  
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Author Jaziar Radianti; Julie Dugdale; Jose J. Gonzalez; Ole-Christoffer Granmo pdf  isbn
openurl 
  Title Smartphone sensing platform for emergency management Type Conference Article
  Year 2014 Publication ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2014  
  Volume Issue Pages 379-383  
  Keywords Civil defense; Disasters; Hazards; Information systems; Intelligent systems; Learning systems; Mobile phones; Pattern recognition; Risk management; Sensors; Signal encoding; Emergency management; Human Tracking; Human-centered computing; Mobile sensing; Publish-subscribe; Smartphones  
  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.  
  Address CIEM, University of Agder, Norway; University Pierre Mendès France, Grenoble, France  
  Corporate Author Thesis  
  Publisher The Pennsylvania State University Place of Publication University Park, PA Editor S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih.  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9780692211946 Medium  
  Track Intelligent Systems Expedition Conference 11th International ISCRAM Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 864  
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Author Bogdan Tatomir; Leon J.M. Rothkrantz; Mirela Popa pdf  isbn
openurl 
  Title Intelligent system for exploring dynamic crisis environments Type Conference Article
  Year 2006 Publication Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2006  
  Volume Issue Pages 288-297  
  Keywords Complex networks; Information systems; Intelligent systems; Mobile ad hoc networks; Multi agent systems; Crisis; Emergency; Graph matchings; Infrastructure-less; Manet; Map merging; Topological map; Merging  
  Abstract The routing in complex buildings is provided by information systems. But during a crisis situation, these systems may collapse due to certain incidents like an explosion, a fire or sabotage. The task of guiding people in this situation has to be handled in some way. In this paper we present a possible solution to this problem. We use a multi-agent system in a mobile ad-hoc network, without the need of any infrastructure. The main idea of the paper is that just by exploring the damaged building, the data of the changing environment becomes available and the challenge is how to fuse this data from different observers. We focused on the way of building, sharing and merging topological maps, using observations from individuals present in this infrastructure-less network. Besides a more efficient exploration of the building, the system presented in this paper can provide the rescue teams with additional services like finding the nearest exit. Some results of the tests we run with our system are also presented.  
  Address Delft University of Technology, DecisLab, Delft, NL, Netherlands; Delft University of Technology, Delft, NL, Netherlands  
  Corporate Author Thesis  
  Publisher Royal Flemish Academy of Belgium Place of Publication Newark, NJ Editor B. Van de Walle, M. Turoff  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9090206019; 9789090206011 Medium  
  Track MULTIAGENT SYSTEMS FOR EMERGENCY MANAGEMENT Expedition Conference 3rd International ISCRAM Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 997  
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Author Vitaveska Lanfranchi pdf  openurl
  Title Machine Learning and Social Media in Crisis Management: Agility vs Ethics Type Conference Article
  Year 2017 Publication Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2017  
  Volume Issue Pages 256-265  
  Keywords Machine Learning; Social Media; Intelligent systems; Ethics; Privacy; Mitigation Strategies  
  Abstract One of the most used sources of information for fast and flexible crisis information is social media or crowdsourced data, as the information is rapidly disseminated, can reach a large amount of target audience and covers a wide variety of topics. However, the agility that these new methodologies enable comes at a price: ethics and privacy. This paper presents an analysis of the ethical risks and implications of using automated system that learn from social media data to provide intelligence in crisis management. The paper presents a short overview on the use of social media data in crisis management to then highlight ethical implication of machine learning and social media data using an example scenario. In conclusion general mitigation strategies and specific implementation guidelines for the scenario under analysis are presented.  
  Address OAK Group, Department of Computer Science, University of Sheffield  
  Corporate Author Thesis  
  Publisher Iscram Place of Publication Albi, France Editor Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN Medium  
  Track Ethical, Legal and Social Issues Expedition Conference 14th International Conference on Information Systems for Crisis Response And Management  
  Notes Approved no  
  Call Number Serial 2016  
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Author Felix Wex; Guido Schryen; Dirk Neumann pdf  isbn
openurl 
  Title Intelligent decision support for centralized coordination during Emergency Response Type Conference Article
  Year 2011 Publication 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 Abbreviated Journal ISCRAM 2011  
  Volume Issue Pages  
  Keywords Information systems; Intelligent systems; Optimization; Resource allocation; Allocation mechanism; Comparative analysis; Coordination; Distributed resource allocation; Emergency operations centers; Emergency response systems; Intelligent decision support; Monte-Carlo simulations; Decision support systems  
  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.  
  Address Albert-Ludwigs-Universität Freiburg, Germany; Universität Regensburg, Germany  
  Corporate Author Thesis  
  Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Lisbon Editor M.A. Santos, L. Sousa, E. Portela  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9789724922478 Medium  
  Track Intelligent Systems Expedition Conference 8th International ISCRAM Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 1077  
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