Renán T. Rodríguez, & Víctor A. Bañuls. (2023). Challenges of Emergency Management Digital Transformation in Industrial Parks. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 196–203). Palmerston North, New Zealand: Massey Unversity.
Abstract: Industrial parks are economic drivers of the cities where they are located. These parks are constantly at risk of catastrophe due to the diversity of industries and the dangerous materials used in their production processes. Despite this constant threat, there is a digitization shortfall in the emergency management process in industrial parks. This research paper seeks to describe the importance of digital transformation in industrial parks, as well as, how information systems can contribute to proper emergency management. Based on the preliminary analysis of the literature, it was possible to determine how the implementation of an emergency system would facilitate the prevention of catastrophes according to the analysis of scenarios, simulation, management, and proper coordination of emergencies in real-time. However, the proper functioning of this system depends on the implementation of environmental innovation, exploration, and observation skills, without neglecting the commitment of organizations and their material, human and technological resources to achieve a significant change.
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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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James Hilton, & Nikhil Garg. (2023). Rapid Geospatial Processing for Hazard and Risk Management using the Geostack Framework. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 2–7). Palmerston North, New Zealand: Massey Unversity.
Abstract: Operational predictive and risk modelling of landscape-scale hazards such as floods and fires requires rapid processing of geospatial data, fast model execution and efficient data delivery. However, geospatial data sets required for hazard prediction are usually large, in a variety of different formats and usually require a complex pre-processing toolchain. In this paper we present an overview of the Geostack framework, which has been specifically designed for this task using a newly developed software library. The platform aims to provide a unified interface for spatial and temporal data sets, deliver rapid processing through OpenCL and integrate with web APIs or external graphical user interface systems to display and deliver results. We provide examples of hazard and risk use cases, particularly Spark, a Geostack based system for predicting the spread of wildfires. The framework is open-source and freely available to end users and practitioners in the hazard and geospatial space.
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Michael Erskine, Scott Seipel, & Cayson Seipel. (2022). Development of a Geospatial Agent-Based Simulation of Disaster Evacuations for Battery Electric Vehicle (BEV) Policy. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 532–540). Tarbes, France.
Abstract: Several nations have signaled their intent to phase out petroleum-based engines for passenger vehicles and promote a transition to battery electric vehicles (BEVs). While researchers have established the long-term environmental benefits of BEVs, there are critical considerations for policymakers in areas prone to natural disasters. This research intends to develop a geospatial-based model to explore and simulate the evacuation of BEVs during a disaster. This work-in-progress (WiPe) paper examines the variables essential to creating an effective hurricane simulation. The final simulation model is intended to allow for the evaluation of BEV policy options under a variety of scenarios. We describe the considerations made during the development of this geospatial agent-based simulation under various hurricane parameters. Finally, we mention the expected benefits of our work and hint at possible policy directions.
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Julian Zobel, Ralf Kundel, & Ralf Steinmetz. (2022). CAMON: Aerial-Ground Cooperation System for Disaster Network Detection. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 87–101). Tarbes, France.
Abstract: Information on large-scale disaster areas, like the location of affected civilians, is highly valuable for disaster relief efforts. This information can be collected by an Aerial Monitoring System, using UAVs to detect smart mobile devices carried by civilians. State-of-the-art systems typically rely on a purely passive detection approach. In this paper, we present a cooperative communication system between UAVs and ground-based devices to improve the detection performance of such an Aerial Monitoring System. We provide different approaches for the cooperative information collection and evaluate them in a simulated inner-city scenario. The results highlight the effectiveness of the cooperative system, being able to detect civilian devices in the disaster area faster and more comprehensively than a non-cooperative approach.
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