Alexander Garcia-Aristizabal, Maria Polese, Giulio Zuccaro, Miguel Almeida, & Christoph Aubrecht. (2015). Improving emergency preparedness with simulation of cascading events scenarios. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Natural or man-made disasters can trigger other negative events leading to tremendous increase of fatalities and damages. In case of Low Probability ? High consequences events, decision makers are faced with very difficult choices and the availability of a tool to support emergency decisions would be very much beneficial. Within EU CRISMA project a concept model and tool for evaluating cascading effects into scenario-based analyses was implemented.This paper describes the main concepts of the model and demonstrates its application with reference to two earthquake-triggered CE scenarios, including (the first) the falling of an electric cable, ignition and spreading of forest fire and (the second) the happening of a second earthquake in a sequence. Time dependent seismic vulnerability of buildings and population exposure are also considered for updating impact estimation during an earthquake crisis.
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Artur Ricardo Bizon, Luciana P. de Araújo Kohler, Adilson Luiz Nicoletti, Fernanda Dal Bosco, Murilo Schramm da Silva, & Thales Bohn Pessatti. (2020). Integration statistical systems for land cover mapping in Southern Brazil. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 498–505). Blacksburg, VA (USA): Virginia Tech.
Abstract: The remote sensing is a way to optimize the process of land cover classification allowing that this process will be by high definition images of satellite. For the research it was used the Google Earth Engine with JavaScript programming language to classify the images, identifying the areas with forest or reforest. It was identified that classifiers Random Forest and Logistic Regression have a high performance in classify the images. From them it was developed functions to process automatically of new images with purpose of classify them in relation to land cover.
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Balogh, Z., Gatial, E., Dolatabadi, S. H., Dlugolinský, Štefan, Saltarella, M., Scipioni, M. P., et al. (2023). Communication Protocol for using Nontraditional Information Sources between First Responders and Citizens during Wildfires. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 152–165). Omaha, USA: University of Nebraska at Omaha.
Abstract: One of the biggest challenges faced during the wildfires is communication. A specific case represents the need to establish communication between first responders and the public. This paper presents a proposal for a generic protocol to ensure effective communication between fire fighters and many citizens at the incident site or in the surrounding area using nontraditional information sources such as a dedicated mobile app or social media. Specific challenges, concepts and technologies relevant to such communication are described specifically customized for forest fires and wildfires. The protocol itself is provided by proposing information flows between the involved actors. Moreover, several technologies including a Citizen Engagement Mobile App, an Edge Micro Data Center for forward command centers, a Mesh in the Sky communication infrastructure or a Dashboard integrating and displaying all the data in one place is shortly introduced. The presented paper is a work in progress.
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Peter Berggren, Björn J.E. Johansson, Nicoletta Baroutsi, Isabelle Turcotte, & Sébastien Tremblay. (2014). Assessing team focused behaviors in emergency response teams using the shared priorities measure. 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. 130–134). University Park, PA: The Pennsylvania State University.
Abstract: The purpose of this work in progress paper is to report on the method development of the Shared Priorities measure to include content analysis, as a way of gaining a deeper understanding of team work in crisis/emergency response. An experiment is reported where the performance of six trained teams is compared with the performance of six non-trained teams. The experiment was performed using an emergency response microworld simulation with a forest fire scenario. Dependent measures were simulation performance, the Crew Awareness Rating Scale (CARS), and content analysis. Trained teams performed better and scored higher on measures of team behaviors.
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Daniel Hahn. (2007). Non-restrictive linking in wireless sensor networks for industrial risk 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. 605–609). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The OSIRIS project addresses the disaster management workflow in the phases of risk monitoring and crisis management. Risk monitoring allows the continuous observation of endangered areas combined with sensor deployment strategies. The crisis management focuses on particular events and the support by sensor networks. Four complementary live demonstrations will validate the OSIRIS approach. These demonstrations include water contamination, air pollution, south European forest fire, and industrial risk monitoring. This paper focuses on the latter scenario: the industrial risk monitoring. This scenario offers the special opportunity to demonstrate the relevance of OSIRIS by covering all the aspects of monitoring, preparation and response phases of both environmental risk and crisis management. The approach focuses on non-restrictive linking in a wireless sensor network in order to facilitate the addition and removal of nodes providing open interaction primitives allowing the comfortable integration, exclusion, and modification. A management layer with an event-triggered and service-based middleware is proposed. A live lab with real fire is illustrated.
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María Hernandez, Susana Montero, David Díez, Ignacio Aedo, & Paloma Díaz. (2009). Towards an interoperable data model for forest fire reports. 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: The creation of action statistics of fire extinction services is a common activity in the management of forest-fires emergencies. The compilation of action data and the elaboration of statistics based upon those data allow drawing relevant information about forest fires emergencies and fire extinction services. The creation of action statistics requires the exchange of heterogeneous data, with different granularity and detail, among scattered sources. This paper introduces a Forest Fire Report Data Model devoted to be a data reference model for sharing and exchanging forest fire reports in order to achieve syntactic interoperability among independent systems. The definition of the model has been based on the review of forest fire statistics made by different agencies as well as the experience gained in developing an information system, called SIU6, for the creation of action reports of.
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María Hernandez, Susana Montero, David Díez, Paloma Díaz, & Ignacio Aedo. (2010). A data transfer protocol for forest fire statistics: Achieving interoperability among independent agencies. 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 elaboration of statistics after a catastrophic situation allows us not only to analyze the economic, ecological and social impact of the event but also to improve the emergency management process. One compelling example of data collection for statistics is forest fires. The agencies involved in providing data have its own systems to collect data and mechanisms to send them, as well as, its data format for storing. Since such mechanisms are usually proprietary, and in order to normalize the exchange of data with statistics generating systems, a data transfer protocol should be used. In this paper we present a data transfer protocol called Forest Fire Statistics Protocol (FFSP). This protocol aims at transmitting consolidated forest fire data between independent agencies. The data transferred are based on the Forest Fire Report Data Model. Both mechanisms are based on open standards providing both technical interoperability and a solution that might be developed once and fit the needs of all. FFSP has been implemented as a web service over SOAP, SSL/TLS and TCP protocols.
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Yasir Javed, Tony Norris, & David Johnston. (2012). Evaluating SAVER: Measuring shared and team situation awareness of emergency decision makers. 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: Large scale emergencies are usually responded to by a team of emergency managers or a number of sub teams for safety and efficiency. Team coordination has attracted considerable research interest, especially from the cognitive, human factors, and ergonomic aspects because shared situation awareness (SSA) and team situation awareness (TSA) of team members are critical for optimal decision making. This paper describes the development of an information system (SAVER) based on SSA and TSA oriented systems design. Validation and evaluation of the implemented design show that decision performance is improved by the SAVER system. © 2012 ISCRAM.
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Jenny Marklund, & Cecilia Hull Wiklund. (2016). Learning from C2 Situations in the Field – Identifying Lessons from a Major Forest Fire in Sweden. 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: In July 2014, Sweden?s full crisis response system engaged in a major operation as a small forest fire spun out of control, turning into the largest forest fire in Sweden in modern times. A number of investigations have been undertaken to understand the course of the fire and identify lessons for future crisis management. This paper presents one approach to identifying such lessons, the lessons learned process applied by the Swedish Armed Forces. The paper also highlights some of the major crisis response lessons from the fire, the most important being the failure to learn from lessons identified after previous forest fires. Results also show that the crisis response effort was negatively affected by a poor understanding of relevant actor?s competencies and resources, as well as lack of continuity in the initial chain of command, and identifies the need for national prioritization of resources at times of major crises.
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Jingxian Wang, Lida Huang, Guofeng Su, Tao Chen, Chunhui Liu, & Xiaomeng Wang. (2021). UAV and GIS Based Real-time Display System for Forest Fire. 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. 527–535). Blacksburg, VA (USA): Virginia Tech.
Abstract: When a forest fire occurs, the commander cannot obtain information in time, and the rescue command is like groping in the dark. In order to solve the problem, this research establishes a real-time forest fire display system based on UAV and GIS. The UAV is equipped with visible light and thermal imaging cameras to transmit back forest fire scenes in real time. Based on GIS, the system can extract the boundary of the fire field through image processing and 3D modeling technology, and display various forest fire information on the screen. Through image processing and 3D modeling technology, the boundary of the fire field can be extracted and displayed on the screen. We conducted several experiments to test the accuracy and the reliability of the system. The result shows that the accuracy, reliability and real-time capability can be guaranteed in small-scale forest fires.
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Björn J.E. Johansson, Jiri Trnka, & Rego Granlund. (2007). The effect of geographical information systems on a collaborative command and control task. 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. 191–200). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper tests the claimed benefits of using geographical information systems (GIS) in emergency response operations. An experimental study comparing command teams using GIS and paper-based maps is presented. The study utilized a combined approach using microworld simulations together with physical artefacts. Participants in the experiment took the role of command teams, facing the task of extinguishing a simulated forest fire. A total of 132 persons, forming 22 teams, participated in the study. In eleven of the teams, the participants were given access to GIS with positioning of fire-brigades as well as sensor data about the fire outbreak. In the other eleven teams, the participants were using paper-based maps. The result shows that teams using GIS performed significantly better than teams with paper-based maps in terms of saved area. Communication volume was considerably reduced in the case of GIS teams. Implications of these results on GIS are discussed as well as methodological considerations for future research.
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Kyriaki Christaki, Dimitrios Tsiakmakis, Ivanka Babic, Guillaume Inglese, Konstantinos Konstantoudakis, Gabriele Giunta, et al. (2022). Augmented Reality Points of Interest for Improved First Responder Situational Awareness. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 755–770). Tarbes, France.
Abstract: Situational awareness is a vital component of any disaster response mission, both in terms of first responder (FR) safety and efficiency. Points of interest (POI) can pertain to hazards known beforehand, risks discovered during the course of a mission, victims, entry and exit routes, important equipment, and more. Although communications and technical means can expand an individual FR’s situational awareness, they depend on clarity and can increase cognitive load, as this expanded volume of information must be held in each FR’s memory. Augmented reality (AR) can visualize POIs in context with the environment in a clear and intuitive way and reduce cognitive load as the don’t rely on a user’s memory. This paper presents an AR solution for FR team situational awareness, comprising four interconnected and collaborating situational awareness tools sharing a common pool of virtual POIs, alongside a range of different functionalities particular to each.
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Stefan Moellmann, David Braun, Hagen Engelmann, & Wolfgang Raskob. (2011). Key performance indicator based calculations as a decision support for the tactical level. 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: For the planning of relief operations the duration and the necessary resources are key factors for a successful completion. Those factors, however, are difficult to estimate due to the large number of influencing factors in a complex crisis situation. This paper presents a software module that supports the planning by calculating the duration and the required resources for relief measures based on key performance indicators (KPI). It is part of a project called SECURITY2People aiming to develop the basics for an integrated disaster management system. The module consists of an easy to use tool to calculate the timing of a relief measure when applied to a given disaster site. In addition it contains a detailed view to display and edit the model of the selected measure which is depicted as a Gantt chart and forms the basis of the calculation. Finally, the paper describes how this module can benefit from interoperability with other modules of this project and existing systems and services.
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Mojir, K. Y., Maceviciute, E., Olson, N., Gatial, E., & Balogh, Z. (2023). Citizen Engagement in wildfire management: needs, challenges, methods and framework. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 761–772). Omaha, USA: University of Nebraska at Omaha.
Abstract: With climate change, the frequency and spread of wildfires have intensified globally, bearing disastrous impacts on wildlife, the economy, and human well-being. Efforts on broad fronts are required, including proactive public participation. However, studies related to citizen engagement in the context of wildfire management remain limited. Therefore, there is a need for further studies in this area. This paper reports on ongoing work conducted in the context of an H2020 project called SILVANUS. The study investigates the methods, practices, needs and challenges related to citizen engagement in wildfire management. The authors have developed a tentative citizen engagement framework, and preliminary results related to citizens' needs and challenges are presented. The study identifies relevant topics, training contents, and methods that can be used for public engagement in wildfire management. The paper contributes towards designing future engagement modalities, technologies and training materials related to wildfire management and potentially even other crises.
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Simon Mulwa Mutie, Banci Mati, Hussein Gadain, & Patrick Home. (2005). Land cover change effects on flow regime of mara river. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 237–246). Brussels: Royal Flemish Academy of Belgium.
Abstract: The transboundary Mara River across Kenya and Tanzania and draining in to Lake Victoria has undergone major anthropogenic changes affecting its land cover over the past 50 years. However, these changes have not been quantified in a manner to allow wider scale understanding of the causative factors, their effects and show hot spots that required immediate intervention. To address these issues, a study of the land use/land cover change was done based on interpretation of digital LANDSAT TM and ETM images of 1986 and 2000 respectively with Idrisi Kilimanjaro software. In a separate addition, analyses of hydrological factors was done which involved comparing monthly mean flow hydrographs to assess changes in flow characteristics of the Mara river immediately after the basin forests. The results obtained showed 2.3 % deforestation, 0.7% reforestation, 20.9% of the basin was opened up for agriculture and 7.5% changed to wetlands. Hydrological investigations showed that river flow regimes have changed, with sharp increases in peaks, attenuation of the river hydrographs and reduction in base flows, factors that could not be linked to changes in rainfall amounts and characteristics but related to modifications of the land surface induced by artificial influences of the man in the basin.
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Nguyen Bang Tran, Mihai Tanase, Lauren Bennett, & Cristina Aponte. (2018). Evaluation of spectral indices for assessing fire severity in Victorian temperate forests, Australia. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 213–222). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: ABSTRACT Victorian temperate forests, characterized by variable wildfire response traits, such an analysis is missing hindering fire impact estimation over large areas on operational basis. To close this gap, we have evaluated 10 remotely sensed indices across eight areas affected by wildfires in 1998, 2006, 2007, and 2009 which comprise 13 forest types. The analysis was carried out at forest type level and as a function of the regeneration strategies (seeders, basal and epicormic reporters) and structure (tree height and canopy cover) with the six forest groups. Index performance was evaluated by (i) examining index response across four fire severity levels, (ii) the separability index, and (iii) the optimality values analysis. A ranking scoring system was used to compare the index performance to distinguish among severity classes. Initial results demonstrated that there hasn't been a consistency of the best indices capacity but there a consistently worse index among forest groups.
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Julio Camarero Puras, & Carlos A. Iglesias. (2009). Disasters2.0. Application of Web2.0 technologies in emergency situations. 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 article presents a social approach for disaster management, based on a social portal, so-called Disasters2.0, which provides facilities for integrating and sharing user generated information about disasters. The architecture of Disasters2.0 is designed following REST principles and integrates external mashups, such as Google Maps. This architecture has been consumed with different clients, including a mobile client, a multiagent system for assisting in the decentralized management of disasters, and an expert system for automatic assignment of resources to disasters. As a result, the platform allows seamless collaboration of humans and intelligent agents, and provides a novel web2.0 approach for multiagent and disaster management research.
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Giorgio Rascioni, Susanna Spinsante, Ennio Gambi, & Daniele Falcone. (2008). DTT technology for rural communities alerting. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 12–17). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The transition from analog to digital television broadcasting has opened the way to a number of new services, enabled by the advanced potentialities offered by interactive applications. Considering the wide diffusion of TV receivers among people living both in towns and rural areas, and how many people, either old or young, educated or not, are familiar with the TV box, it is reasonable to exploit such a capillary and widespread technology to reach immediately and directly almost the total population in a certain area. Among the possible applications, emergency and alert information dissemination can play a vital role in improving the communities response and reaction to natural or man made disasters. Focusing on this topic, this paper proposes an alert dissemination service exploiting an MHP interactive application developed ad hoc for DVB-T broadcasting, to force the direct delivery of emergency information to TV users.
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Reza Mazloom, HongMin Li, Doina Caragea, Muhammad Imran, & Cornelia Caragea. (2018). Classification of Twitter Disaster Data Using a Hybrid Feature-Instance Adaptation Approach. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 727–735). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Huge amounts of data that are generated on social media during emergency situations are regarded as troves of critical information. The use of supervised machine learning techniques in the early stages of a disaster is challenged by the lack of labeled data for that particular disaster. Furthermore, supervised models trained on labeled data from a prior disaster may not produce accurate results, given the inherent variation between the current and the prior disasters. To address the challenges posed by the lack of labeled data for a target disaster, we propose to use a hybrid feature-instance adaptation approach based on matrix factorization and the k nearest neighbors algorithm, respectively. The proposed hybrid adaptation approach is used to select a subset of the source disaster data that is representative for the target disaster. The selected subset is subsequently used to learn accurate Naive Bayes classifiers for the target disaster.
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Simone Wurster, Frank Fiedrich, Michael Klafft, & Andreas Bohn. (2016). Sudden Cardiac Arrest and the Role of Crowd Tasking Apps for Risk Mitigation. 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: Sudden cardiac arrest (SCA) is among the three most prominent causes of death in industrialized nations. Therefore, experts are calling for solutions, including smartphone-based systems to mobilize volunteers. German researchers are developing a crisis response system with a crowd tasking app. It aims to help reduce the effects of large-scale events, but also of ad-hoc incidents including SCA. This paper describes an approach to determine the potential of the system to increase the survival rate of SCA illustrated by an example. Its concept was analyzed by five experts from three countries and benefited from their feedback.
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Sofia Eleni Spatharioti, Sara Wylie, & Seth Cooper. (2018). Identifying and Assessing Points of Interest through Crowdsourced Image Analysis. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1123–1125). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: During a natural disaster, major damages to critical structures such as bridges or power lines can severely disrupt community functions for long periods of time, making the task of swiftly identifying this type of damage vital for response and recovery. However, survey flight paths are often designed with a main focus of complete and quick coverage of affected areas through aerial photography, which is then assigned to volunteers to aid in damage report and labeling. We designed a crowdsourcing interface that focuses on locating points of interest and assessing damage using images from survey flights. We tested our design using a disaster and a non-disaster application by recruiting volunteers on Amazon Mechanical Turk. We found that the type of structure may cause difficulties for crowd workers in providing accurate assessments and that designing flights to also target structures may provide higher quality imagery for this type of task.
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Tobias Andersson Granberg, Sara Erlander, David Fredman, Lovisa Olovsson, & Emma Persson. (2022). Predicting Volunteer Travel Time to Emergencies. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 44–54). Tarbes, France.
Abstract: A model is developed, which can predict the travel time for volunteers that are dispatched as first responders to emergencies. Specifically, the case of lay responders to out of hospital cardiac arrest is studied. Positions from historical responses is used to estimate the real response times, which are used to train and evaluate the new travel time model. The new model considers the road network and the transport mode most likely used by the volunteers. The results for the new model are compared to a model used in an existing volunteer initiative. They show that the new model can make better predictions in 59.7% of the cases. This can be used directly as a base for improving the travel time estimates in existing volunteer initiatives, and to improve the input data to the continuously evolving volunteer resource management systems.
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Sébastien Tremblay, Peter Berggren, Martin Holmberg, Rego Granlund, Marie-Eve Jobidon, & Paddy Turner. (2012). A multiteam international simulation of joint operations in crisis response. 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: Concepts such as trust, shared understanding, cultural differences, mental workload, and organizational structure all impact upon the effectiveness of an organization (e.g., Tindale & Kameda, 2000), and even more so in the context of large scale multinational operations (e.g, Smith, Granlund, & Lindgen, 2010). In order to study these concepts we plan a multinational, distributed experiment with participants from three nations collaborating in the same virtual environment: Canadian, British, and Swedish participants will work together as part of a multinational MTS to deal with a complex task and gain control of a crisis situation. Empirical research on MTS remains limited (see, e.g., DeChurch & Marks, 2006) particularly at the multinational level where the investigation of MTS has been so far focused on case studies and exercises (e.g., Goodwin, Essens, & Smith, 2012). Therefore, there is a need to empirically study multinational MTS in order to assess the specific issues that multinational operations face, notably cultural and languages differences. The simulation environment used as experimental platform for this project is C3Fire (www.c3fire.org, Granlund & Granlund, 2011). C3Fire creates an environment whereby teams must work together to resolve a crisis in the firefighting domain, with the goal of evacuating people in critical areas, putting out the forest fire, and protecting buildings and other areas of value from the burning forest fire. This platform makes it possible to study participants' collaborative processes when dealing with a set of crisis scenarios in the context of a simulated emergency response situation. To deal efficiently with the crisis management operation, participants need to prioritize between different objectives, identify and protect critical areas, and plan and implement activities based on given resources. All these tasks are distributed between team members, compelling participants to exchange information and coordinate within and between teams to execute the task. The task is divided into three areas of responsibility as follows: 1) Information and Planning, responsible for situation assessment and providing the operating picture; 2) Operation and Logistic, responsible for intervention and resource management; and 3) Search and Rescue, responsible for research and management of civilians. C3Fire is designed to: 1) achieve an optimal compromise between internal and external validity; 2) show flexibility in scenario configuration (spectrum of units and roles – including search and rescue functions; Tremblay et al., 2010), allowing researchers to capture emergency response and crisis management and rapid response planning; 3) be highly configurable for testing many different types of teams (e.g., hierarchical vs. horizontal organizations); and 4) readily provide objective, non-intrusive metrics for assessing teamwork effectiveness (including macrocognitive functions and team processes) as well as quantitative measures of task performance (that take into account conflicting mission goals). © 2012 ISCRAM.
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Yasir Imtiaz Syed, Raj Prasanna, S Uma, Kristin Stock, & Denise Blake. (2018). A Design Science based Simulation Framework for Critical Infrastructure Interdependency. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 516–524). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: Critical Infrastructures (CI) such as electricity, water, fuel, telecommunication and road networks are a crucial factor for secure and reliable operation of a society. In a normal situation, most of the businesses operate on an individual infrastructure. However, after major natural disasters such as earthquakes, the conflicts and complex interdependencies among the different infrastructures can cause significant disturbances because a failure can propagate from one infrastructure to another. This paper discusses the development of an integrated simulation framework that models interdependencies between electricity and road infrastructure networks of Wellington region. The framework uses a damage map of electricity network components and integrates them with road access time to the damaged components for determining electricity outage time of a region. The results can be used for recovery planning, identification of vulnerabilities, and adding or discarding redundancies in an infrastructure network.
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Zelenka, J., Kasanický, T. š, Gatial, E., Balogh, Z., Majlingová, A., Brodrechtova, Y., et al. (2023). Coordination of Drones Swarm for Wildfires Monitoring. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 144–151). Omaha, USA: University of Nebraska at Omaha.
Abstract: As a result of climate change and global weather patterns, large forest fires are becoming more frequent in different parts of the world. The focus of the presented work is on creation of a complex coordination and communication framework for a swarm of drones specially tailored for use in preventing and monitoring of forest fires. The presented algorithm has been testing and evaluating using a computer simulation. The testing and validation in relevant environment is scheduled during a pilot demonstration exercise with real personnel and equipment, which will take place in Slovakia on April 2023. The presented work is a part of the SILVANUS EU H2020 project, whose objective is the creation of a climate resilient forest management platform for forest fire prevention and suppression. SILVANUS draws on environmental, technical, and social science experts to support regional and national authorities responsible for forest fire management in their respective countries.
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