Gkika, I., Pattas, D., Konstantoudakis, K., & Zarpalas, D. (2023). Object detection and augmented reality annotations for increased situational awareness in light smoke conditions. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 231–241). Omaha, USA: University of Nebraska at Omaha.
Abstract: Innovative technologies powered by Computer Vision algorithms can aid first responders, increasing their situ ational awareness. However, adverse conditions, such as smoke, can reduce the efficacy of such algorithms by degrading the input images. This paper presents a pipeline of image de-smoking, object detection, and augmented reality display that aims to enhance situational awareness in smoky conditions. A novel smoke-reducing deep learning algorithm is applied as a preprocessing step, before state-of-the-art object detection. The detected objects and persons are highlighted in the user’s augmented reality display. The proposed method is shown to increase detection accuracy and confidence. Testing in realistic environments provides an initial evaluation of the method, both in terms of image processing and of usefulness to first responders.
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Holzhüter, M., Huhle, G., Reuter-Oppermann, M., Hellriegel, J., & Klafft, M. (2023). Acceptance study on application systems to improve situational incident management through bi-directional communication between citizens and decision-makers in emergencies and crises situations. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 197–207). Omaha, USA: University of Nebraska at Omaha.
Abstract: Efficient hazard prevention and disaster control depend on situational awareness. Situational information is – among others – provided by citizens on the ground. Disaster managers are often reluctant to use such information on a large scale or in a systematic way for fear of being overwhelmed by information overload in a stressful crisis. New information technologies for crisis management are strongly dependent on the acceptance of the people using them and can only be successful as socio-technical systems. Therefore, 354 employees of public and private emergency operation centres as well as members of crisis management teams were asked to assess different information sharing technologies. 504 people from the public responded to an online survey about their willingness to use such technologies. The results indicate a high level of acceptance by both user groups for bi directional communication technologies for situation management and the improvement of situational awareness.
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Jack Pagotto, & Darrell O'Donnell. (2012). Canada's multi-agency situational awareness system – Keeping it simple. 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: The Canadian Multi-Agency Situational Awareness System (MASAS) is rapidly becoming Canada's national system for exchanging emergency management incident-relevant information amongst multiple agencies and jurisdictions. Through the use of structured information aligned with open standards, and a centrally managed open architecture, MASAS provides a trusted virtual community with the ability to seamlessly exchange emergency management information. MASAS offers an information exchange architecture that is based around a highly resilient system of data aggregation hubs that are easily accessible directly or through third party commercial tools by emergency management officials at all levels, from the smallest community in the most remote areas of Canada's north to key federal stakeholders such as the federal Government Operations Centre or the Canadian military. This paper highlights the key design principles, experimental activities, and technology implementation strategies that are positioning MASAS as a Canadian success story in the making – from coast to coast to coast. © 2012 ISCRAM.
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Jonathan L. Barr, Annie M. Boek Peddicord, Russ Burtner, & Heidi A. Mahy. (2011). Current domain challenges in the emergency response community. 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: This paper describes the development of a framework targeted to technology providers to better understand the grand domain challenges of the emergency response and management community (EM). In developing this framework, Pacific Northwest National Laboratory (PNNL) researchers interviewed subject matter experts (SMEs) across the EM domain and corroborated these findings with current literature. We are presently examining relationships and dependencies within the framework. We anticipate that a thorough understanding of these gaps and dependencies will allow for a more informed approach to prioritizing research, developing tools, and applying technology to enhance performance in the EM community.
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Justine I. Blanford, Jase Bernhardt, Alexander Savelyev, Gabrielle Wong-Parodi, Andrew M. Carleton, David W. Titley, et al. (2014). Tweeting and tornadoes. 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. 319–323). University Park, PA: The Pennsylvania State University.
Abstract: Social Media and micro-blogging is being used during crisis events to provide live up-to-date information as events evolve (before, during and after). Messages are posted by citizens or public officials. To understand the effectiveness of these messages, we examined the content of geo-located Twitter messages (“tweets”) sent during the Moore, Oklahoma tornado of May 20th, 2013 (+/-1day) to explore the spatial and temporal relationships of real-time reactions of the general public. We found a clear transition of topics during each stage of the tornado event. Twitter was useful for posting and retrieving updates, reconstructing the sequence of events as well as capturing people's reactions leading up to, during and after the tornado. A long-term goal for the research reported here is to provide insights to forecasters and emergency response personnel concerning the impact of warnings and other advisory messages.
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Kenneth Joseph, Peter M. Landwehr, & Kathleen M. Carley. (2014). An approach to selecting keywords to track on twitter during a disaster. 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. 672–676). University Park, PA: The Pennsylvania State University.
Abstract: Several studies on Twitter usage during disasters analyze tweets collected using ad-hoc keywords pre-defined by researchers. While recent efforts have worked to improve this methodology, open questions remain about which keywords can be used to uncover tweets contributing to situational awareness (SA) and the quality of tweets returned using different terms. Herein we consider a novel methodology for uncovering relevant keywords one can use to search for tweets containing situational awareness. We provide a description of the methodology and initial results which suggest our approach may lead to better keywords to use for keyword searching during disasters.
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Kevin Fall, Gianluca Iannaccone, Jayanthkumar Kannan, Fernando Silveira, & Nina Taft. (2010). A disruption-tolerant architecture for secure and efficient disaster response communications. 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: We consider the problem of providing situational awareness when citizens in a disaster are willing to contribute their own devices, such as laptops and smart phones, to gather data (text, images, audio or video) and to help forward data gathered by others. A situational awareness service processes all received data and creates annotated maps to visualize a disaster site (e.g., the status of the disaster, such as fires or floods, the location of people, food, or water). We discuss the challenges imposed on such an application when 1) the communications infrastructure in the disaster area can only provide intermittent connectivity, 2) anxious victims generate large amounts of redundant content congesting the network, and 3) the sharing of personal devices creates security and privacy threats. We present an architecture that addresses the requirements to support such a service.
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Kimmo Laakso. (2013). Emergency management: Identifying problem domains in communication. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 724–729). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: In emergency management, the identification of hazards, analysis of risks, development of mitigation and response plans, maintaining of situational awareness and support of response and recovery are all complex responsibilities. A major accident brings together individuals belonging to many different organizations, having backgrounds in different fields of operation, and representing different organizational cultures. They have to absorb a large amount of information about the accident over a short period of time. In order to take effective action, actors are expected to work smoothly together, thus the flow of information from and to the actors involved is crucial. Nevertheless, there are certain problem domains in the different phases of emergency management, which may weaken the flow of information. In this paper we present the findings of the first round of a Delphi study in which we identified problem domains in communication both in long-term and short-term planning for major accidents.
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Kristine Steen-Tveit. (2020). Identifying Information Requirements for Improving the Common Operational Picture in Multi-Agency Operations. 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. 252–263). Blacksburg, VA (USA): Virginia Tech.
Abstract: While there exists a considerable body of literature on the importance of a common operational picture (COP) in multi-agency emergency operations, the COP concept itself still lacks a univocal definition. Despite the lack of consensus regarding the mechanisms underlying the COP, the literature implies a level of consistency in the focus on sharing critical information. Based on interviews with Norwegian emergency management stakeholders, this study investigates common information requirements for emergency management services and presents an example of a framework for structuring the sharing of critical information and building a COP. Termed 'the window report', this framework is used among emergency stakeholders in Norway and Sweden. The study identified eight common information requirement categories for managing extreme weather scenarios. With a focus on common information needs and a process for structured information sharing, future strategic emergency management planning might take a more holistic perspective on cross-sectoral operations than in current practice.
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Kristine Steen-Tveit, & Jaziar Radianti. (2019). Analysis of Common Operational Picture and Situational Awareness during Multiple Emergency Response Scenarios. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Disaster response operations require communication and coordination between agencies that seldom occurs in everyday workday situations. Furthermore, in such hybrid environments it is necessary to establish a common operational picture for the responders involved to support collaborative decision-making. The emergency responders must gain situational awareness, and this can further affect the quality of how they deal with the situation. Training in emergency situations is shown to be efficient for learning. In order to understand the complexity of working in unpredictable environments, an analysis of an audio-log from a large-scale drill was carried out. Moreover, this paper provides a definition of several categories for identifying the processes to establish situational awareness and a common operational picture among emergency responders. The analysis process revealed how the actors communicate and revealed an overall communication pattern.
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Kristine Steen-Tveit, Jaziar Radianti, & Bjørn Erik Munkvold. (2020). SMS-based real-time data collection for evaluation of situational awareness and common operational picture: lessons learned from a field exercise. 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. 276–284). Blacksburg, VA (USA): Virginia Tech.
Abstract: Managing complex multi-agency emergency operations requires that the key actors have a holistic, correct and dynamic situational awareness (SA) and that the involved actors establish a common operational picture (COP). Establishing SA and COP are key objectives in many multi-agency exercises, however, reported research shows limitations in existing methods and approaches for collecting the data required for evaluating this. By being able to capture near real-time information during different phases of the exercise we will be better positioned to identify what works well and what does not work in the process of establishing SA and COP. Our paper presents an example of real-time data collection using SMS during a multi-agency field exercise. Overall, the results support the idea of this as an effective method for collecting real-time data for analyzing the formation of SA and a COP among actors in emergency management.
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Lamsal, R., Read, M. R., & Karunasekera, S. (2023). A Twitter narrative of the COVID-19 pandemic in Australia. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 353–370). Omaha, USA: University of Nebraska at Omaha.
Abstract: Social media platforms contain abundant data that can provide comprehensive knowledge of historical and real-time events. During crisis events, the use of social media peaks, as people discuss what they have seen, heard, or felt. Previous studies confirm the usefulness of such socially generated discussions for the public, first responders, and decision-makers to gain a better understanding of events as they unfold at the ground level. This study performs an extensive analysis of COVID-19-related Twitter discussions generated in Australia between January 2020, and October 2022. We explore the Australian Twitterverse by employing state-of-the-art approaches from both supervised and unsupervised domains to perform network analysis, topic modeling, sentiment analysis, and causality analysis. As the presented results provide a comprehensive understanding of the Australian Twitterverse during the COVID-19 pandemic, this study aims to explore the discussion dynamics to aid the development of future automated information systems for epidemic/pandemic management.
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Laura Petersen, Laure Fallou, Grigore Havarneanu, Paul Reilly, Elisa Serafinelli, & Rémy Bossu. (2018). November 2015 Paris Terrorist Attacks and Social Media Use: Preliminary Findings from Authorities, Critical Infrastructure Operators and Journalists. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 629–638). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Crisis communication is a key component of an effective emergency response. Social media has evolved as a prominent crisis communication tool. This paper reports how social media was used by authorities, critical infrastructure operators and journalists during the terrorist attacks that hit Paris on 13th November 2015. A qualitative study was conducted between January and February 2017 employing semi-structured interviews with seven relevant stakeholders involved in this communication process. The preliminary critical thematic analysis revealed four main themes which are reported in the results section: (1) social media is used in crisis times; (2) authorities gained situational awareness via social media; (3) citizens used social media to help one another; and (4) communication procedures changed after these critical events. In conclusion, authorities, citizens and journalists all turned to social media during the attack, both for crisis communication and for increasing situational awareness.
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Lindsley G. Boiney, Bradley Goodman, Robert Gaimari, Jeffrey Zarrella, Christopher Berube, & Janet Hitzeman. (2008). Taming multiple chat room collaboration: Real-time visual cues to social networks and emerging threads. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 660–668). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Distributed teams increasingly rely on collaboration environments, typically including chat, to link diverse experts for real time information sharing and decision-making. Current chat-based technologies enable easy exchange of information, but don't focus on managing those information exchanges. Important cues that guide face-to-face collaboration are either lost or missing. In some military environments, operators may juggle over a dozen chat rooms in order to collaborate on complex missions. This often leads to confusion, overload, miscommunication and delayed decisions. Our technology supports chat management. A summary display bar reduces the number of chat rooms operators need open by providing high level situational awareness pointers, in real-time, to: a) rooms with increasing message activity levels, b) rooms in which important collaborators are participating (those in the operator's social network), and c) rooms in which operator-selected keywords are used. This ability to peripherally monitor less critical chat rooms reduces operator overload, while enhancing the ability to rapidly detect important emerging discussion threads. © 2008 The MITRE Corporation. All rights reserved.
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Lise Ann St. Denis, Amanda Lee Hughes, Jeremy Diaz, Kylen Solvik, Maxwell B. Joseph, & Jennifer K. Balch. (2020). 'What I Need to Know is What I Don't Know!': Filtering Disaster Twitter Data for Information from Local Individuals. 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. 730–743). Blacksburg, VA (USA): Virginia Tech.
Abstract: We report on the design, development, and evaluation of a user labeling framework for social media monitoring by emergency responders. By labeling Twitter user accounts based on behavior and content, this novel approach identifies tweets from accounts belonging to Individuals generating Personalized content and captures information that might otherwise be missed. We evaluate the framework using training data from the 2018 Camp, Woolsey, and Hill fires. Approximately 30% of the Individual-Personalized tweets contain first-hand information, providing a rich stream of content for social media monitoring. Because it can quickly eliminate most redundant tweets, this framework could be a critical first step in an end-to-end information extraction pipeline. It may also generalize more easily for new disaster events since it relies on general user account attributes rather than tweet content. We conclude with next steps for refining and evaluating our framework in near real-time during a disaster response.
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Ly Dinh, Sumeet Kulkarni, Pingjing Yang, & Jana Diesner. (2023). Reliability of Methods for Extracting Collaboration Networks from Crisis-related Situational Reports and Tweets. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 181–195). Palmerston North, New Zealand: Massey Unversity.
Abstract: Assessing the effectiveness of crisis response is key to improving preparedness and adapting policies. One method for response evaluation is reviewing actual response activities and interactions. Response reports are often available in the form of natural language text data. Analyzing a large number of such reports requires automated or semi automated solutions. To improve the trustworthiness of methods for this purpose, we empirically validate the reliability of three relation extraction methods that we used to construct interorganizational collaboration networks by comparing them against human-annotated ground truth (crisis-specific situational reports and tweets). For entity extraction, we find that using a combination of two off-the-shelf methods (FlairNLP and SpaCy) is optimal for situational reports data and one method (SpaCy) for tweets data. For relation extraction, we find that a heuristics-based model that we built by leveraging word co-occurrence and deep and shallow syntax as features and training it on domain-specific text data outperforms two state-of-the-art relation extraction models (Stanford OpenIE and OneIE) that were pre-trained on general domain data. We also find that situational reports, on average, contain less entities and relations than tweets, but the extracted networks are more closely related to collaboration activities mentioned in the ground truth. As it is widely known that general domain tools might need adjustment to perform accurately in specific domains, we did not expect the tested off-the-shelf tools to perform highly accurately. Our point is to rather identify what accuracy one could reasonably expect when leveraging available resources as-is for domain specific work (in this case, crisis informatics), what errors (in terms of false positives and false negatives) to expect, and how to account for that.
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Maximilian Walther, Sven Schaust, & Michael Kaisser. (2013). Social media-based event detection for crisis management in the al za'atari refugee camp. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 927–928). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Social Media data allows for profound analyses of user-generated content in order to predict or manage disasters and crisis situations. In this paper, we present an analysis of tweets from and about Al Za'atari, a refugee camp in Jordan close to the Syrian border. Our results are based on the analysis of location-tagged tweets by our “Avalanche” system in order to support an accurate situational awareness picture for on-site and off-site operators from relief organizations on evolving events and challenges.
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Muhammad Imran, Shady Elbassuoni, Carlos Castillo, Fernando Díaz, & Patrick Meier. (2013). Extracting information nuggets from disaster- Related messages in social media. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 791–801). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Microblogging sites such as Twitter can play a vital role in spreading information during “natural” or man-made disasters. But the volume and velocity of tweets posted during crises today tend to be extremely high, making it hard for disaster-affected communities and professional emergency responders to process the information in a timely manner. Furthermore, posts tend to vary highly in terms of their subjects and usefulness; from messages that are entirely off-topic or personal in nature, to messages containing critical information that augments situational awareness. Finding actionable information can accelerate disaster response and alleviate both property and human losses. In this paper, we describe automatic methods for extracting information from microblog posts. Specifically, we focus on extracting valuable “information nuggets”, brief, self-contained information items relevant to disaster response. Our methods leverage machine learning methods for classifying posts and information extraction. Our results, validated over one large disaster-related dataset, reveal that a careful design can yield an effective system, paving the way for more sophisticated data analysis and visualization systems.
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Nathan Elrod, Pranav Mahajan, Monica Katragadda, Shane Halse, & Jess Kropczynski. (2021). An Exploration of Methods Using Social Media to Examine Local Attitudes Towards Mask-Wearing During a Pandemic. 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. 345–358). Blacksburg, VA (USA): Virginia Tech.
Abstract: During the COVID-19 health crisis, local public offcials expend considerable energy encouraging citizens to comply with prevention measures in order to reduce the spread of infection. During the pandemic, mask-wearing has been accepted among health offcials as a simple preventative measure; however, some local areas have been more likely to comply than others. This paper explores methods to better understand local attitudes towards mask-wearing as a tool for public health offcials' situational awareness when preparing public messaging campaigns. This exploration compares three methods to explore local attitudes: sentiment analysis, n-grams, and hashtags. We also explore hashtag co-occurrence networks as a starting point to begin the filtering process. The results show that while sentiment analysis is quick and easy to employ, the results oer little insight into specific local attitudes towards mask-wearing, while examining hashtags and hashtag co-occurrence networks may be used a tool for a more robust understanding of local areas when attempting to gain situational awareness.
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Naveen Ashish, & Sharad Mehrotra. (2010). Community driven data integration for emergency response. 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: This paper describes our work in progress on an approach and technology for providing integrated data access in situational awareness applications – particularly for disaster and emergency response. The key new aspect of our work is an approach where information aggregation, processing, and integration capabilities are offered as a service to any new application builder. Further, we provide a framework for possibly reusing prior information integration knowledge, the development of which demands the major fraction of time and complexity in a new application, in a customized fashion for new application. Our overall goal is to provide a framework where integrated access to critical data in an emergency response situation can be enabled very rapidly and by personnel with basic IT and data handling expertise. Our approach, while general purpose, is currently motivated by and grounded in the context of situational awareness systems for incident commander decision support in the fire response domain.
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Nitesh Bharosa, Jaco Appelman, & Peter De Bruin. (2007). Integrating technology in crisis response using an information manager: First lessons learned from field exercises in the Port of Rotterdam. 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. 63–70). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Integrating information technology (IT) in crisis management networks is a difficult and long-term endeavor. First responders must establish situational awareness and take decisions under time pressure with incomplete information. Partly, this can be mitigated by adopting more advanced IT, however practice shows that adoption is hampered because of the required change in routines and procedures. We believe that we can moderate a change in routines and stimulate the adoption of technology by introducing a new role: the information manager (IM). This paper presents some results of the first round of field observations. The main conclusion is that the IM is instrumental where it concerns, speeding up the process of establishing situational awareness and improving the information structures. In order to further improve the production of situational awareness we suggest that further research should address the issues of the internalization of process guidelines and enhancing the adaptability of information systems.
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Norman Groner, & Charles Jennings. (2012). Describing pipeline emergency response communications using situational awareness informational requirements and an informational flow analyses. 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: The Christian Regenhard Center for Emergency Response Studies at John Jay College, CUNY, has begun work on developing best practices for hazardous material pipeline emergency response plans. The approach involves modeling a generic goal-based interagency emergency communications system using a two-step process. First, a situational awareness information requirements analysis will describe the informational requirements essential to an effective emergency response. The requirements analysis involves a goal decomposition approach where the information requirements are related to actionable decisions, goals and emergency response roles. Second, an information flow analysis will informational sources and means to provide required information. The same panel of experts will complete both analyses. Once the communications system is described, a separate Delphi group will use a failure modes and effects analysis (FMEA) to estimate the criticality of the components described in the situational awareness requirements and information flow analyses. © 2012 ISCRAM.
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Oleg Aulov, Adam Price, & Milton Halem. (2014). AsonMaps: A platform for aggregation visualization and analysis of disaster related human sensor network observations. 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. 802–806). University Park, PA: The Pennsylvania State University.
Abstract: In this paper, we describe AsonMaps, a platform for collection, aggregation, visualization and analysis of near real-time, geolocated quantifiable information from a variety of heterogeneous social media outlets in order to provide emergency responders and other coordinating federal agencies not only with the means of listening to the affected population, but also to be able to incorporate this data into geophysical and probabilistic disaster forecast models that guide their response actions. Hurricane Sandy disaster is examined as a use-case scenario discussing the different types of quantifiable information that can be extracted from Instagram and Twitter.
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Paul S. Earle, & David J. Wald. (2006). Rapid post-earthquake information and assessment tools from the U.S. geological survey national earthquake information center. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 402–408). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: A suite of post-earthquake information products and assessment tools are produced and distributed by the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC). These products range from the rapid determination of earthquake magnitude and location to tools that provide situational awareness following earthquake catastrophes. The NEIC distributes earthquake location, magnitude, and supporting information through many sources including, text message, pager, and the Internet (e-mail, web-pages and RSS feeds). To aid in the rapid determination of an earthquake's impact, the NEIC has developed tools to 1) map the observed shaking intensity reported from the region affected by the earthquake (Community Internet Intensity Maps), and 2) quantify the number of people exposed to severe shaking (Prompt Assessment of Global Earthquakes for Response).
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Paulini, M. S., Duran, D., Rice, M., Andrekanic, A., & Suri, N. (2023). KENNEL Threat Detection Boxes for First Responder Situational Awareness and Risk Management. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 208–219). Omaha, USA: University of Nebraska at Omaha.
Abstract: KENNEL is a deployable IoT-based system consisting of a network of unattended ground sensors, known as Threat Detection Boxes (TDBs), which may be outfitted with any variety of custom and commercial-off-the-shelf sensors for hazard detection. The KENNEL system fills a technological gap for sensor fusion, interpretation, and real-time alerting via existing information management systems, such as Team Awareness Kit (TAK). First responders face a critical need for improved situational awareness, detection, and response to hazardous events. KENNEL provides a first of its kind, low-cost sensing & data fusion platform that is highly extensible, configurable, and self-sustaining, opening a world of modernization and innovation possibilities across the first responder domain. TDBs may also be statically or ad hoc deployed, improving flexibility, stand-off hazard detection, and resilience in the operational domain. From critical infrastructure monitoring to wearables, the system affords timeliness of critical information for effective risk management and increased personnel safety.
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