Leorey Marquez, Pawan Gamage, Dhirendra Singh, Vincent Lemiale, Trevor Dess, Peter Ashton, et al. (2023). SEEKER: A Web-Based Simulation Tool for Planning Community Evacuations. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 8–24). Palmerston North, New Zealand: Massey Unversity.
Abstract: Bushfires cause widespread devastation in Australia, one of the most fire-prone countries on earth. Bushfire seasons are also becoming longer and outbreaks of severe bushfires are occurring more often. This creates the problem of having more people at risk in very diverse areas resulting in more difficult mass evacuations over time. The Barwon Otway region in Victoria’s Surf Coast Shire is one such area with evacuation challenges due to its limited routes in and out of coastal areas and its massive population surges during the tourist season and holiday periods. The increasing gravity of the bushfire threat to the region has brought about the Great Ocean Road Decision Support System (GOR-DSS) project, and the subsequent development of a disaster evacuation tool to support emergency management organisations assess evacuation and risk mitigation options. This paper describes the design and development of SEEKER (Simulations of Emergency Evacuations for Knowledge, Education and Response). The SEEKER tool adds another level of intelligence to the evacuation response by incorporating agent-based modelling and allows emergency management agencies to design and run evacuation scenarios and analyse the risk posed by the fire to the population and road network. Furthermore, SEEKER can be used to develop multiple evacuation scenarios to investigate and compare the effectiveness of each emergency evacuation plan. This paper also discusses the application of SEEKER in a case study, community engagement, and training.
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Yaniv Mordecai, & Boris Kantsepolsky. (2018). Intelligent Utilization of Dashboards in Emergency Management. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1108–1119). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Effective decision-supporting visualization is critical for strategic, tactic, and operational management before and during a large-scale climate or extreme weather emergency. Most emergency management applications traditionally consist of map-based event and object visualization and management, which is necessary for operations, but has small contribution to decision makers. At the same time, analytical models and simulations that usually enable prediction and situation evaluation are often analyst-oriented and detached from the operational command and control system. Nevertheless, emergencies tend to generate unpredictable effects, which may require new decision-support tools in real-time, based on alternative data sources or data streams. In this paper, we advocate the use of dashboards for emergency management, but more importantly, we propose an intelligent mechanism to support effective and efficient utilization of data and information for decision-making via flexible deployment and visualization of data streams and metric displays. We employ this framework in the H2020 beAWARE project that aims to develop and demonstrate an innovative framework for enhanced decision support and management services in extreme weather climate events.
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Fatemeh Hendijani Fard, Cooper Davies, & Frank Mauer. (2017). Agile Emergency Responses Using Collaborative Planning HTN. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 857–867). Albi, France: Iscram.
Abstract: Emergency response planning is a complex task due to multiple organizations involved, different planning considerations, etc. Using artificial intelligence collaborative planning helps in the automatic planning for complex situations. Analyzing all impacting factors along with plans that are executable can facilitate the decision making in Emergency Operations Centers for an agile emergency response. A main component of a planner is a knowledge base. Although many systems are developed to support decision making in emergency response or recovery, they either focus on specific or small organizations, or rely on simulations. To the best of our knowledge, there is a gap that there is no common knowledge base for provincial level mass emergencies for automatic planners. The multiplicity of the emergency response documents and their structure makes the knowledge acquisition complex. In this paper, we explain the process of extracting knowledge based on hierarchical task networks and how it speeds up the reactivity to a disaster.
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Melanie Eckle, João Porto de Albuquerque, Benjamin Herfort, Alexander Zipf, Richard Leiner, Rüdiger Wolff, et al. (2016). Leveraging OpenStreetMap to Support Flood Risk Management in Municipalities: A Prototype Decision Support System. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Floods are considered the most common and devastating type of disasters world-wide. Therefore, flood management is a crucial task for municipalities- a task that requires dependable information to evaluate risks and to react accordingly in a disaster scenario. Acquiring and maintaining this information using official data however is not always feasible, especially for smaller municipalities. This issue could be approached by integrating the collaborative maps of OpenStreetMap (OSM). The OSM data is openly accessible, adaptable and continuously updated. Nonetheless, to make use of this data for effective decision support, the OSM data must be first adapted to the needs of decision makers. In the pursuit of this goal, this paper presents the OpenFloodRiskMap (OFRM)- a prototype for a OSM based spatial decision-support system. OFRM builds an intuitive and practical interface upon existing OSM data and services to enable decision makers to utilize the open data for emergency planning and response.
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Mohd Khairul Azmi Hassan, & Yun-Heh Chen-Burger. (2016). Communication and Tracking Ontology Development for Civilians Earthquake Disaster Assistance. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
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.
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