Chanvi Kotak, Brian Tomaszewski, & Erik Golen. (2018). 3-1-1 Calls Hot Spot Analysis During Hurricane Harvey: Preliminary Results. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 350–361). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Hurricane Harvey caused massive damage and necessitated the need for identification of areas under high risk. During Harvey, the city of Houston received more than 77000, 3-1-1 calls for assistance. Due to damage caused to the infrastructure, it became difficult to handle and respond to the crisis. Geographic Information Systems (GIS) is a vital technology to assist with real-time disaster monitoring. we investigated if a correlation could be found between 311 data calls made during the Hurricane Harvey and aerial images captured during the event, specifically to see if 311 data could be ground-truthed via hot spot analysis. Preliminary results indicate that visual representation of 3-1-1 call data can aid in analyzing the expected areas of high traffic of calls for assistance and plan an effective way to manage resources. Future work will involve more in-depth analysis of combined 3-1-1 call data with satellite imagery using image classification techniques.
|
Ilan Noy, Jacob Pastor Paz, Olga Filippova, & Ken Elwood. (2018). A Building Inventory for Seismic Policy in an Earthquake-Prone City. 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. 145–152). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: We describe the creation of a building inventory database that is created for Wellington, New Zealand's earthquake-prone capital city. This database aims to assist the generation of research on the risks, impacts, and viable solutions for reducing the seismic risk of existing multi-story concrete buildings in Wellington's Central Business District. The database includes structural, economic and market information on every building in the CDB. Its primary purpose is to inform a multi-disciplinary project whose aims are: (1) to provide best scientific knowledge about the expected seismic performance of concrete buildings; (2) to assess the impact of multiple building failures including the downstream consequences of associated cordoning; (3) to provide a path for seismic retrofitting that includes prioritization of retrofits; and (4) to inform the design of a regulatory structure that can facilitate the reduction of risk associated with earthquake vulnerable concrete buildings as described in aims (1)-(3).
|
Min Zhu, Ruxue Chen, Shi Chen, Shaobo Zhong, Cheng Liu, Tianye Lin, et al. (2018). A Conceptual Double Scenario Model for Predicting Medical Service Needs in the International Disaster Relief Action. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 409–418). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Man-made and natural disasters have affected people worldwide. Mass casualty incidents would create a surge in demand for medical services. Medical service needs are the basis of medical strategic readiness plan. In recent years, international actions have been criticized for being ill-adapted to dominating health needs of the affected region. The “Scenario-Response” modeling is an important method in disaster prediction. This research established a medical service needs scenario model with two different levels of ambition: a disaster scenario, in which casualty figure, composition of injuries are constrained by the types of the disaster as well as the degree of the damage, and a country scenario, in which the healthcare needs are constrained by the health coverage and the health condition of local people. Armed conflicts in Yemen and Syria Arab Republic were analyzed by this model. The results showed that the outcome of this model fit the reality.
|
Dick Ooms, Willem-Jan van den Heuvel, & Bartel Van de Walle. (2018). A Conceptual Framework for Civil-Military Interaction in Peace Support Operations. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1003–1015). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In complex emergencies, civil and military organizations often find themselves being partners in an international effort aimed at peace keeping, humanitarian relief, and development support. Civil and military partners need to exchange information and to cooperate as required. This assumes effective and efficient Civil-Military Interaction (CMI). However, CMI research literature shows that, in practice, this is far from a reality. In particular, our research indicates that deficiencies in knowledge processes and knowledge management within international civil and military organizations contribute to the causes of ineffective and inefficient CMI. Our research aims to investigate the feasibility of developing technical solutions exploiting knowledge engineering, to support fieldworkers in overcoming these CMI problems. As a first step, this paper introduces a Conceptual Framework (CF) that captures reference models of the CMI domain. The CF has been developed to analyze CMI problems and underlying KM deficiencies. It is being illustrated, explored and validated using real-world case studies.
|
Ioan M. Ciumasu. (2018). A coordination lattice model for building urban resilience. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 419–427). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Common denominators emerge difficultly in projects bridging science and society or/and across disciplines. Managing crises require inter-organizational learning and citizen involvement, but, often such undertakings lead to bargain resulting in sub-optimal decisions. Building resilience into human communities demands complex projects, which further require good problem definition, starting with agreements on values and knowledge, as basis for further agreements on goals and methods. This paper spreads the Data-Information-Knowledge-Action-Result frame over a 4-level process to generate a DIKAR_process matrix and lattice that allows optimal orientation and coordination towards achieving a set of common denominators and coordinated action protocols. This framework allows sequences and cycles that can be formulated and pursued simultaneously, comparatively and iteratively, within any large, heterogeneous constituency of actors involved in building resilience in local communities. The model is illustrated and discussed in relation to urban sustainability issues and complementary methods like knowledge maps, mental models, social learning and scenarios.
|
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.
|
Rohit Valecha, Onook Oh, & H. Raghav Rao. (2018). A Model for Assessing Label Quality in Crowdsourced Crisis Mapping Systems: A Case of 2010 Haiti Earthquake. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (1161). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: This poster is dedicated to present our research work on the application of crowd and crowdsourcing platforms to crisis situations. In particular, it focuses on crowdsourced crisis mapping solutions. Crowdsourcing has become a popular avenue of research dealing with crisis mapping systems. Crisis mapping systems enable collecting and disseminating crisis information. The contribution of this research is to create a model to assess label quality in the context of crowdsourced crisis mapping. The model was devised in three phases: (1) collection of crisis reports from a crisis mapping platform, (2) crowd-sourced empirical approach to capture labels at scale, and (3) a theory-guided approach for feature selection to create a machine learning model. In the first phase, we collected crisis reports from the Ushahidi platform during the 2010 Haiti earthquake. In the second phase, we utilized CrowdFlower – a crowdsourcing platform for labeling crisis reports based on the input from five crowd volunteers. In the third phase, we adopted situation awareness lens for selecting contextual and collaborative features.
|
Miriam Klein, Eric Rigaud, Marcus Wiens, Anouck Adrot, Frank Fiedrich, Nour Kanaan, et al. (2018). A Multi-Agent System for Studying Cross-Border Disaster Resilience. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 135–144). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Resilience to disasters depends on measures taken before, during and after the occurrence of adverse events. These measures require interactions between people belonging to different organizations (public, private, non-profit) and citizens in normal and stressful situations. The efficiency of resilience measures results from the collective interaction of individuals, groups of individuals, and organizations, as well as the situational characteristics of the decision environment. The aim of the French-German research project INCA is to develop a decision support framework for improving cross-border area resilience to disasters. This project comprises the design and the implementation of a multi-agent system with the objective to study the behavioral and organizational implications of cross-border cooperation for crisis management and disaster resilience. The analyzed measures focus on citizens who require medical support and the integration of volunteers into the crisis management procedure. This paper outlines the potentials of the multi-agent system and provides first implementation insights.
|
Quentin Schoen, Sebastien Truptil, Matthieu Lauras, Aurelie Conges, & Franck Fontanili. (2018). A new approach of monitoring system for Supply Chain management during crisis. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1140–1142). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Sensitive products supply chain and supply chain facing crisis management share several aspects. In both cases, several decision makers have to choose the best options most of the time under pressure, often in emergency and need to access numerous information from the field. This shared monitoring aspect put forward the visualization need to consider in each decision all the crisis potential impacts. Unfortunately, for the transportation steps we focus on, the current transport management systems do not reach these requirements. In this paper, focusing on supply chains during crisis situations, we present a new monitoring system with adapted functionalities. The added value is to connect in real time and relevant way the data from the field to the information on a shared model used to make reliable decisions. We use the French Blood Establishment supply chain to illustrate the proposition.
|
Nicoletta Baroutsi. (2018). A Practitioners Guide for C2 Evaluations: Quantitative Measurements of Performance and Effectiveness. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 170–189). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Quantitative evaluations are valuable in the strive for improvements and asserting quality. However, the field of Command & Control (C2) evaluations are hard to navigate, and it is difficult to find the correct measurement for a specific situation. A comprehensive Scoping Study was made concerning measurements of C2 performance and effectiveness. A lack of an existing appropriate framework for discussing C2 evaluations led to the development of the Crisis Response Management (CRM) Matrix. This is an analysis tool that assigns measurements into categories, and each category display unique strengths, weaknesses and trends. The analysis yielded results proving to be too rich for a single article, thusly, this is the first of two articles covering the results. In this article, the Practitioners Guide focus on results valuable for someone interested in evaluating C2. Each evaluation has specific requirements that, for best result, ought to be reflected in the chosen measurement.
|
Laura Laguna Salvadó, Matthieu Lauras, & Tina Comes. (2018). A Sustainability Maturity Assessment Method for the Humanitarian Supply Chain. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 276–290). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: The HSC is a key element for the success of HOs relief operations. Today, the HSC performance faces many challenges: (1) the increasing gap between funding and needs; (2) donors ask for more transparency and accountability; (3) the growing urgency of switching to sustainable development is gaining ground in public opinion. Consequently, to maintain a competitive position (order winner) in the near future, considering sustainability in addition to effectiveness and efficiency to measure the performance of the operations becomes fundamental. In the literature, some authors have highlighted that the lack of Decision Support Systems difficult the planning and achievement of sustainability performance objectives in humanitarian operations. Therefore, we propose a sustainability maturity assessment method to improve the sustainability of HSC operations. Using the information gathered from IFRC field research, as well as from the literature, a proof of concept is presented to demonstrate the relevance of the proposal.
|
Firoj Alam, Ferda Ofli, Muhammad Imran, & Michael Aupetit. (2018). A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 553–572). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: People increasingly use microblogging platforms such as Twitter during natural disasters and emergencies. Research studies have revealed the usefulness of the data available on Twitter for several disaster response tasks. However, making sense of social media data is a challenging task due to several reasons such as limitations of available tools to analyze high-volume and high-velocity data streams. This work presents an extensive multidimensional analysis of textual and multimedia content from millions of tweets shared on Twitter during the three disaster events. Specifically, we employ various Artificial Intelligence techniques from Natural Language Processing and Computer Vision fields, which exploit different machine learning algorithms to process the data generated during the disaster events. Our study reveals the distributions of various types of useful information that can inform crisis managers and responders as well as facilitate the development of future automated systems for disaster management.
|
Hans Julius Betke. (2018). A Volunteer Coordination System Approach for Crisis Committees. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 786–795). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In disaster situations security authorities and organizations have the responsibility and duty to manage the disaster response. These organizations work in elaborated command and control structures with well trained employees. But in recent events, supported by new technologies like social media and mobile devices, spontaneous volunteers from the local population gained new importance as helpful force in disaster response. The high amount of volunteers bears high potentials to improve the efficiency of several activities through pure manpower. However, these people are not integrated in existing structures and lack a proper qualification. The proper coordination of spontaneous volunteers poses new challenges for disaster authorities. In this paper we introduce the prototype of a novel information system enabling crisis committees to coordinate spontaneous volunteers by semi-automated purposive communication and allocation. The results of first staff exercises are discussed to emphasize potential benefits and open challenges.
|
Andrew Flaws, & Chris Purchas. (2018). A Web GIS Tool for Disaster Waste Management Planning in New Zealand. 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. 272–278). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: To date, the management of waste-streams generated by natural and anthropogenic disasters in New Zealand has been ad hoc, with planning largely taking place post rather than pre event. A valid reason for this is that the severity and consequences of such events varies widely, dictating the type and quantity of waste produced. To help mitigate problems caused by unplanned waste, a web GIS tool is being developed for use in a pre-event planning exercise and for developing quick early estimates of waste during an event. The tool models the amount of waste generated by different types of natural disasters, quantifying the amount of waste for different waste-streams. The user can then find the nearest suitable waste disposal location, accounting for barriers. This tool could be of great value for local government. It is flexible, so that can quickly and simply be extended to other regions and the intention is for regional councils to host the tool within their own GIS environment.
|
Hans Christian Augustijn Wienen, Faiza Allah Bukhsh, Eelco Vriezekolk, & Roel J. Wieringa. (2018). Accident Analysis Methods and Models – a Systematic Review. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 398–408). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: After a risk has manifested itself and has led to an accident, valuable lessons can be learned that can be taken into account to reduce the risk of a similar accident occurring again. This calls for accident analysis methods. In the past 20 years a large number of accident analysis methods have been proposed and it is difficult to find the right method to apply in a specific circumstance. We conducted a review of the state of the art of accident analysis methods and models across domains. We classify the models using the well-known categorization into sequential, epidemiological and systemic methods. We find that these classes have their own characteristics in terms of speed of application versus pay-off. For optimum risk reduction, methods that take organizational issues into account can add valuable information to the risk management process in an organization.
|
Ahmed S. Khalaf, Poom Pianpak, Sultan A. Alharthi, Zahra NaminiMianji, Ruth Torres, Son Tran, et al. (2018). An Architecture for Simulating Drones in Mixed Reality Games to Explore Future Search and Rescue Scenarios. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 971–982). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: The proliferation of unmanned aerial systems (i.e., drones) can provide great value to the future of search and rescue. However, with the increase adoption of such systems, issues around hybrid human-drone team coordination and planning will arise. To address these early challenges, we provide insights into the development of testbeds in the form of mixed reality games with simulated drones. This research presents an architecture to address challenges and opportunities in using drones for search and rescue. On this architecture, we develop a mixed reality game in which human players engage with the physical world and with gameplay that is purely virtual. We expect the architecture to be useful to a range of researchers an practitioners, forming the basis for investigating and training within this unique, new domain.
|
Changwon Son, Jukrin Moon, S. Camille Peres, & Farzan Sasangohar. (2018). An Episode as a Trace of Resilient Performance in Multi-Agency Incident Management Systems. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 942–948). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In order to cope with increasing complexity of catastrophic disasters, resilience is considered an essential capability of an incident management system (IMS). As resilience is manifested during systems operation, a naturalistic observational study was conducted to understand how resilient performance dynamically takes place in this domain. The study results were presented using the concept of episodes, each of which uncovers a trace of such resilient performance following an information input called an inject. The episode analysis also facilitated the identification of complex and dynamic interactions among human and technological agents to satisfy work demands, representing work-as-done (WAD) in large-scale emergency response operations.
|
Jun Hu, Xueming Shu, & Shiyang Tang. (2018). Analysis of Core Social Actors in Nine Types of Mass Incidents Based on Social Network Analysis. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 219–231). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: This article studies on the cases of nine types of mass incidents happened in China during the last decade, and study the relationships among various social actors in different types of mass incidents with the methods of social networks from the perspective of relational theory. By constructing the social network of mass incidents, we statistically analyze the relationship intensity between social actors in different types of mass incidents, and calculate the centrality degrees of social actors, which can be regard as index to characterize the social risk of social actors. Meanwhile, we also analyze the cliques and “core-periphery” structure in the social network of mass incidents to get the core social actors in mass incidents, thus providing decision-making references for social leaders to effectively deal with mass incidents and improving emergency response capabilities.
|
Jacob L. Graham, & Mark B. Stephens. (2018). Analytic Decision Gaming – A Tool to Develop Crisis Response and Clinical Reasoning. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 60–68). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Emerging threats provide motivation to develop new methods for preparing the next generation of crisis responders. Bayesian theory shifts reasoning toward a probabilistic, epistemic paradigm, giving rise to Evans' revised heuristic-analytic theory. Researchers at The Pennsylvania State University use scenario-based training and the analytic decision game (ADG) to blend and implement these processes as foundational pedagogy for engaging, educating and training medical students as crisis responders and critical thinkers. The ADG scenarios vary by content and level of expertise, lending themselves readily adaptable to both crisis response preparation and the development of clinical reasoning. The ADG creates a virtual crisis requiring participants to engage in scenario management as role-players. For the past two years, medical students from the Penn State College of Medicine, in their first year of training, have participated in the ADG Lights Out scenario, testing community preparation and resilience after a wide-spread and months-long power outage.
|
Stefan Schauer, Stefan Rass, Sandra König, Thomas Grafenauer, & Martin Latzenhofer. (2018). Analyzing Cascading Effects among Critical Infrastructures. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 428–437). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In this article, we present a novel approach, which allows not only to identify potential cascading effects within a network of interrelated critical infrastructures but also supports the assessment of these cascading effects. Based on percolation theory and Markov chains, our method models the interdependencies among various infrastructures and evaluates the possible consequences if an infrastructure has to reduce its capacity or is failing completely, by simulating the effects over time. Additionally, our approach is designed to take the intrinsic uncertainty into account, which resides in the description of potential consequences a failing critical infrastructure might cause, by using probabilistic state transitions. In this way, not only the critical infrastructure's risk and security managers are able to evaluate the consequences of an incident anywhere in the network but also the emergency services can use this information to improve their operation in case of a crisis and anticipate potential trouble spots.
|
Marcus Dombois, Timo Bittner, & Uwe Rüppel. (2018). Approaching the criticality of information for emergency response and control center operations. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 388–397). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Successful emergency response and control center operations rely on a great number of information sources. The importance of said information becomes immediately obvious if it is not available when required during an emergency situation. This can be described as the criticality of information, signifying a potential need for action to prepare for functional failures. The concept described in this paper approaches the criticality via an analysis that examines various combinations of information sources and situations in order to identify weaknesses and improve existing procedures. The proposed semi-quantitative assessment was developed taking several attributes and characteristics of criticality into account and afterwards conducted in close cooperation with emergency response institutions.
|
Magdalena Granåsen, Mari Olsén, & Per-Anders Oskarsson. (2018). Assessing Interorganizational Crisis Response Capability – Initial Results of a Systematic Literature Review. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 190–202). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: The ability to learn from crises is vital in order to strengthen the capability of societies to manage severe events. This paper presents the initial analysis of a systematic literature review regarding capability assessment of inter-organizational crisis management systems. Inter-organizational crisis management capability is a diverse concept, touching on several related concepts such as resilience, situation awareness and operational performance. During a systematic review process 73 publications were identified. The different aspects of crisis management capability found in the publications were clustered, using an exploratory approach. Nine thematic clusters were identified: interaction, relationships, coordination/C2, system performance, preparedness, situation awareness, resilience, decision making and information infrastructure. A conclusion is that crisis response capability encompasses a multitude of aspects associated with a wide range of assessment methods. The identified publications to a large extent explored aspects of collaboration and coordination, while the actual outcome (system performance) was less explored.
|
Shane Errol Halse, Aurélie Montarnal, Andrea Tapia, & Frederick Benaben. (2018). Bad Weather Coming: Linking social media and weather sensor data. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 507–515). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In this paper we leverage the power of citizen supplied data. We examined how both physical weather sensor data (obtained from the weather underground API) and social media data (obtained from Twitter) can serve to improve local community awareness during a severe weather event. A local tornado warning was selected due to its small scale and isolated geographic area, and only Twitter data found from within this geo-locational area was used. Our results indicate that during a severe weather event, an increase in weather activity obtained from the local weather sensors does correlate with an increase in local social media usage. The data found on social media also contains additional information from, and about the community of interest during the event. While this study focuses on a small scale event, it provides the groundwork for use during a much larger weather event.
|
Anastasios Karakostas, Stefanos Vrochidis, Yiannis Kompatsiaris, Boris Kantsepolsky, Jürgen Moßgraber, Stamatia Dasiopoulou, et al. (2018). beAWARE: Enhancing Decision Support and Management Services in Extreme Weather Climate Events. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1136–1139). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In every disaster and crisis, incident time is the enemy, and getting accurate information about the scope, extent, and impact of the disaster is critical to creating and orchestrating an effective disaster response and recovery effort. The main goal of beAWARE framework is to provide support in all the phases of an emergency incident. More specifically, we propose an integrated solution to support forecasting, early warnings, transmission and routing of the emergency data, aggregated analysis of multimodal data and management the coordination between the first responders and the authorities.
|
Briony Gray, Mark Weal, & David Martin. (2018). Building Resilience in Small Island Developing States: Social Media during the 2017 Atlantic Hurricane Season. 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. 469–479). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: There are growing concerns that future Atlantic hurricane seasons will be severe and unpredictable due to underlying factors such as climate change. The 2017 season may offer a range of lessons, especially to small island developing states (SIDS), who are looking to build community resilience and heighten community engagement to cope with disaster. While many SIDS utilise a range of media and technology for these purposes, there has been a recent uptake in the use of social media, which may have further potential to support their goals. This paper scopes the use and users of social media in the case of Antigua and Barbuda during the 2017 Atlantic hurricane season. Through a series of qualitative interviews it explains the role that social media currently has, and concludes with suggestions for its improvement in future seasons that are contextualized over the disaster lifecycle phases.
|