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	Author	Cendrella Chahine; François Peres; Thierry Vidal; Mohamad El Falou
	Title	Functional and Dysfunctional Modelling and Assessment of an Emergency Response Plan			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	363-375
	Keywords	Crisis management; risk analysis; FMECA; BPMN; emergency response plan
	Abstract	The objective of crisis management is to limit the impact of a feared event that has occurred and to restore the conditions corresponding to a nominal situation. In this context, we will focus on emergency response plans for mass casualty crises. In this paper, we propose a functional modelling of the French generic emergency plan, ORSEC plan, using the Business Process Model and Notation (BPMN). On the basis of this representation, a dysfunctional analysis is performed from a new approach identifying Failure mode, effects and criticality analysis (FMECA), in order to better anticipate, the events likely to interrupt the intervention plan. This work will then be used in a multi-agent dynamic planning and scheduling model to allow an actor to choose among the dynamic planning approaches the one that allows him/her to reach his/her goal.
	Address	ULF Liban/LGP-ENIT
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Command and Control Studies	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2424
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	Author	Cendrella Chahine; Thierry Vidal; Mohamad El Falou; François Pérès
	Title	Multi-Agent Dynamic Planning Architectures for Crisis Rescue Plans			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	243-255
	Keywords	Multi-agent systems; planning and scheduling; uncertainty; coordination
	Abstract	We are interested in rescue management in crises such as in terrorist attacks. Today, there are emergency plans that take into account all the stakeholders involved in a crisis depending on the event type, magnitude and place. Unfortunately, they do not anticipate the evolution of the crisis situation such as traffic and hospital overcrowding. In addition, decisions are taken after the information has been passed from the operational level to higher levels. This work focuses on the operational level of the emergency plan. What will happen if the actors at this level, can make certain decisions without escalating the information to higher levels? To answer this question, a multi-agent dynamic planning approach is proposed and it will be tested in two different architectures in order to see how much autonomy can be given to an agent and how they coordinate to save the victims.
	Address	ULF Liban/LGP-ENIT; LGP-ENIT; ULF Tripoli; LGP-ENIT
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2414
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	Author	Chalioris, C.E.; A. Papadopoulos, N.; Sapidis, G.; C. Naoum, M.; Golias, E.
	Title	EMA-based Monitoring Method of Strengthened Beam-Column Joints			Type	Conference Article
	Year	2023	Publication	Proceedings of the 20th International ISCRAM Conference	Abbreviated Journal	Iscram 2023
	Volume		Issue		Pages	853-873
	Keywords	Structural Health Monitoring (SHM); Beam-Column Joint (BCJ); Carbon Fiber-Reinforced Polymer (C-FRP) Ropes; Hierarchical Clustering; Piezoelectric Lead Zirconate Titanate (PZT) Transducers.
	Abstract	Reinforced concrete (RC) beam-column joints (BCJ) are crucial structural components, primarily during seismic excitations, so their structural health monitoring (SHM) is essential. Additionally, BCJ of existing old RC frame structures usually exhibits brittle behavior due to insufficient transverse reinforcement. To alter the brittle behavior of BCJ, an innovative reinforcing technique has been employed, accompanied by a real-time SHM system. Carbon fiber-reinforced polymer (C-FRP) rope as near surface-mounted (NSM) reinforcement has been utilized as external reinforcement of the column and the joint panel. The use of piezoelectric lead zirconate titanate (PZT) transducers for real-time SHM of BCJ sub-assemblages was investigated. Statistical damage indices, such as RMSD and MAPD, were employed to quantify the damage. Furthermore, an innovative approach based on hierarchical clustering was introduced. The experiment results revealed that the damage level of the reference and the retrofitted specimens were successfully diagnosed with PZT transducers.
	Address	Democritus University of Thrace; Democritus University of Thrace; Democritus University of Thrace; Democritus University of Thrace; Democritus University of Thrace
	Corporate Author				Thesis
	Publisher	University of Nebraska at Omaha	Place of Publication	Omaha, USA	Editor	Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi
	Language	English	Summary Language		Original Title
	Series Editor	Hosssein Baharmand	Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition	1
	ISSN		ISBN		Medium
	Track	Infrastructure Health Monitoring During Crises and Disaster	Expedition		Conference
	Notes	http://dx.doi.org/10.59297/PEEC4879			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2571
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	Author	Chanthujan Chandrakumar; Raj Prasanna; Max Stephens; Marion Lara Tan; Caroline Holden; Amal Punchihewa; Julia S. Becker; Seokho Jeong; Danuka Ravishan
	Title	Algorithms for Detecting P-Waves and Earthquake Magnitude Estimation: Initial Literature Review Findings			Type	Conference Article
	Year	2023	Publication	Proceedings of the ISCRAM Asia Pacific Conference 2022	Abbreviated Journal	Proc. ISCRAM AP 2022
	Volume		Issue		Pages	138-155
	Keywords	Earthquake Early Warning; P-Waves; Magnitude Estimation; EEW Algorithms
	Abstract	Earthquake Early Warning System (EEWS) plays a major role during an earthquake in alerting the public and authorities to take appropriate safety measures during an earthquake. Generally, EEWSs use three types of algorithms to generate alerts during an earthquake; namely: source-based, ground motion or wavefield-based and on-site-based approaches. However, source-based algorithms are commonly used in most of EEWSs worldwide. A source-based EEWS uses a particular time frame of the P-wave of an earthquake to estimate the source parameters such as magnitude and the location of that earthquake with the support of P-wave detection and earthquake magnitude and location estimation algorithms. As the initial step of a research project which aims to explore the best use of P-waves to generate earthquake alerts, this Work in Progress paper (WiPe) presents the initial partial findings from an ongoing literature review on exploring the algorithms used for P-wave detection and earthquake magnitude estimation.
	Address	Massey University; Massey University; University of Auckland; Massey University; SeismoCity; ADP Consultancy; Massey University; Changwon National University; Synopsys
	Corporate Author				Thesis
	Publisher	Massey Unversity	Place of Publication	Palmerston North, New Zealand	Editor	Thomas J. Huggins, V.L.
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Track	Building Disaster Resilience	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2488
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	Author	Chauhan, A.
	Title	Humor-Based COVID-19 Twitter Accounts			Type	Conference Article
	Year	2023	Publication	Proceedings of the 20th International ISCRAM Conference	Abbreviated Journal	Iscram 2023
	Volume		Issue		Pages	417-427
	Keywords	COVID-19; Twitter; Humor; Crisis Named Resources
	Abstract	Crisis Named Resources (or CNRs) are social media pages and accounts named after a crisis event. Using the COVID-19 Pandemic as a case study, we identified and examined the role of CNRs that shared humor on Twitter. Our analyses showed that humor-based CNRs shared virus-related rumors, stigma, safety measures, opinions, sarcasm, and news updates. These resources also shared the overall anger and frustration over the year 2020. We conclude by discussing the critical role of humor based CNRs in crisis response.
	Address	Concordia University of Edmonton
	Corporate Author				Thesis
	Publisher	University of Nebraska at Omaha	Place of Publication	Omaha, USA	Editor	Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi
	Language	English	Summary Language		Original Title
	Series Editor	Hosssein Baharmand	Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition	1
	ISSN		ISBN		Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes	http://dx.doi.org/10.59297/YHDI4576			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2536
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	Author	Cheng Wang; Benjamin Bowes; Arash Tavakoli; Stephen Adams; Jonathan Goodall; Peter Beling
	Title	Smart Stormwater Control Systems: A Reinforcement Learning Approach			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	2-13
	Keywords	Reinforcement Learning, Stormwater, Flooding Control.
	Abstract	Flooding poses a significant and growing risk for many urban areas. Stormwater systems are typically used to control flooding, but are traditionally passive (i.e. have no controllable components). However, if stormwater systems are retrofitted with valves and pumps, policies for controlling them in real-time could be implemented to enhance system performance over a wider range of conditions than originally designed for. In this paper, we propose an autonomous, reinforcement learning (RL) based, stormwater control system that aims to minimize flooding during storms. With this approach, an optimal control policy can be learned by letting an RL agent interact with the system in response to received reward signals. In comparison with a set of static control rules, RL shows superior performance on a wide range of artificial storm events. This demonstrates RL's ability to learn control actions based on observation and interaction, a key benefit for dynamic and ever-changing urban areas.
	Address	Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-1	ISBN	2411-3387	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	cw8xk@virginia.edu			Approved	no
	Call Number				Serial	2202
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	Author	Christian Iasio; Ingrid Canovas; Elie Chevillot-Miot; Tendry Randramialala
	Title	A New Approach to Structured Processing of Feedback for Discovering and Investigating Interconnections, Cascading Events and Disaster Chains			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	285-298
	Keywords	Knowledge management; multiperspectivity; lessons learning; crisis management
	Abstract	Post-disaster information processing is relevant for the continuous improvement of operations and the reductionof risks. The current methodologies for post-disaster review suffer from several limitations, which reduce their use as a way of translating narrative in data for qualitative and quantitative analysis. Learning or effective knowledge sharing need a common formalism and method. Ontologies are the reference tool for structuring information in a “coded” data structure. Using the investigation of disaster management during the 2017 hurricane season in the French West Indies within the scope of the ANR “APRIL” project, this contribution introduces a methodology and a tool for providing a graphical representation of experiences for post-disaster review and lessons learning, based on a novel approach to case-based ontology development.
	Address	BRGM; LATTS – Université Gustave Eiffel,Marne la Vallée; Institut des Hautes Etudes du Ministère de l’Intérieur; BRGM
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2418
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	Author	Christina Tsouti; Eleni Ntzioni; Efstathia Tsarouchi; Dimitris Sakellariou; Marios Kotoulas; Christina Papadaskalopoulou; Katerina Valta; Anastasios Karakostas
	Title	Preparedness against Hazardous Events: A Novel Tool for Water Utilities			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	185-199
	Keywords	Crisis management; tool; preparedness; assessment
	Abstract	Various terms and approaches currently exist on outlining the constituent components of crisis management as well as their interrelations, focusing mainly on the effective communication between the members of the crisis management unit. A gap emerges regarding a high-level and holistic approach on crisis management that will have the organization’s preparedness as its main pillar. In this work, crisis is organized into three macro-stages, i.e., pre-crisis, crisis, post-crisis. Preparedness is conceptualized as an overarching concept that frames an organization’s crisis management approach to reduce its vulnerability in a potential crisis. The study focuses on developing a high-level tool to enhance the preparedness of water utilities. The tool aims to serve as a holistic crisis management framework to support stakeholders in qualitatively assessing and improving their level of preparedness. The “Preparedness against hazardous events” tool was the result of this work, which was positively assessed through experts’ evaluation.
	Address	DRAXIS Environmental SA; DRAXIS Environmental SA; DRAXIS Environmental SA; DRAXIS Environmental SA; DRAXIS Environmental SA; DRAXIS Environmental SA; DRAXIS Environmental SA; DRAXIS Environmental SA
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Applications, Tools and Components for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2409
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	Author	Christoph Lamers
	Title	Electronic Visualization for Situational Awareness in Control Rooms			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	1008-1011
	Keywords	Situational Awareness; Situation Map; Command and Control; Visualization
	Abstract	It is generally agreed in crisis management that a comprehensive visualization of the situation is crucial for an appropriate situational awareness of the staff personnel in control rooms. Therefore an expert group of fire officers in the German State North Rhine Westphalia developed a system for this purpose known as the “tactical wall”. The core of the system is a situation map of the relevant area with so-called tactical signs, i. e. defined graphic symbols for hazards, response units and tactical measures. Moreover, the assignment of response units to tactical sectors or staging areas as well as other relevant information such as the management organization is displayed at defined places within the wall. While the system was purely manual in its original version, a new digital version was recently developed. The user interfaces of this system are web-based and can by intuitively operated after a minor training effort.
	Address	State Fire Service Institute North Rhine Westphalia
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Technologies for First Responders	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2466
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	Author	Clara Le Duff; Jean-Philippe Gitto; Julien Jeany; Raphaël Falco; Matthieu Lauras; Frederick Benaben
	Title	A Physics-based Approach to Evaluate Crisis Impacts on Project Management			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	134-143
	Keywords	Crisis Management, Project Management, Risk Assessment, Physics of Decision, Simulation
	Abstract	Project management has become a standard in business. Unfortunately, the projects as well as companies are increasingly subject to major disruptions. In this context, it is of prime importance to have the ability to manage the risks inherent to these projects to best achieve their objectives. The existing approaches of crisis management in the literature no longer seem to be adapted to this new normality. The future of research lies in a more systematic crisis assessment and a better conceptualization of the uncertainty associated with risks. It is necessary to rely on the collection of heterogeneous data in order to maximize the understanding of the project environment and to find a way that best describes and visualizes the influence of crises on the project management processes. This article uses the POD approach and applies it in the context of project management to address these issues.
	Address	Centre Génie Industriel – IMT Mines Albi; Scalian; Scalian; Scalian; Scalian; Centre Génie Industriel – IMT Mines Albi
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2404
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	Author	Claudio Paliotta; Klaus Ening; Sigurd Mørkved Albrektsen
	Title	Micro indoor-drones (MINs) for localization of first responders			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	881-889
	Keywords	Micro indoor-drones, Indoor localisation, Swarm
	Abstract	In this paper, we describe our approach to the localization in GNSS-denied and risky unknown environments offirst responders (FRs). The INGENIOUS project is an EU funded project which is developing a new integratedtoolkit to support the operations of FRs. The micro indoor-drones (MINs) developed within the INGENIOUSproject represent a component of the toolkit which will support the localization of FRs in search-and-rescue (SAR)operations. In this paper, the concept behind the MINs and the current achievements are illustrated.
	Address	SINTEF Digital; SINTEF Digital; SINTEF Digital
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Technologies for First Responders	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	claudio.paliotta@sintef.no			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2380
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	Author	Cody Buntain; Richard Mccreadie; Ian Soboroff
	Title	Incident Streams 2021 Off the Deep End: Deeper Annotations and Evaluations in Twitter			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	584-604
	Keywords	Emergency Management; Crisis Informatics; Twitter; Categorization; Priorization; Multi-Modal; Public Safety; PSCR; TREC
	Abstract	This paper summarizes the final year of the four-year Text REtrieval Conference Incident Streams track (TREC-IS), which has produced a large dataset comprising 136,263 annotated tweets, spanning 98 crisis events. Goals of this final year were twofold: 1) to add new categories for assessing messages, with a focus on characterizing the audience, author, and images associated with these messages, and 2) to enlarge the TREC-IS dataset with new events, with an emphasis of deeper pools for sampling. Beyond these two goals, TREC-IS has nearly doubled the number of annotated messages per event for the 26 crises introduced in 2021 and has released a new parallel dataset of 312,546 images associated with crisis content – with 7,297 tweets having annotations about their embedded images. Our analyses of this new crisis data yields new insights about the context of a tweet; e.g., messages intended for a local audience and those that contain images of weather forecasts and infographics have higher than average assessments of priority but are relatively rare. Tweets containing images, however, have higher perceived priorities than tweets without images. Moving to deeper pools, while tending to lower classification performance, also does not generally impact performance rankings or alter distributions of information-types. We end this paper with a discussion of these datasets, analyses, their implications, and how they contribute both new data and insights to the broader crisis informatics community.
	Address	University of Maryland, College Park (UMD); University of Glasgow; National Institute of Standards and Technology (NIST)
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2441
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	Author	Cody Buntain; Richard Mccreadie; Ian Soboroff
	Title	Incident Streams 2020: TRECIS in the Time of COVID-19			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	621-639
	Keywords	Emergency Management, Crisis Informatics, Twitter, Categorization, Prioritization, COVID-19
	Abstract	Between 2018 and 2019, the Incident Streams track (TREC-IS) has developed standard approaches for classifying the types and criticality of information shared in online social spaces during crises, but the introduction of SARS-CoV-2 has shifted the landscape of online crises substantially. While prior editions of TREC-IS have lacked data on large-scale public-health emergencies as these events are exceedingly rare, COVID-19 has introduced an over-abundance of potential data, and significant open questions remain about how existing approaches to crisis informatics and datasets built on other emergencies adapt to this new context. This paper describes how the 2020 edition of TREC-IS has addressed these dual issues by introducing a new COVID-19-specific task for evaluating generalization of existing COVID-19 annotation and system performance to this new context, applied to 11 regions across the globe. TREC-IS has also continued expanding its set of target crises, adding 29 new events and expanding the collection of event types to include explosions, fires, and general storms, making for a total of 9 event types in addition to the new COVID-19 events. Across these events, TREC-IS has made available 478,110 COVID-related messages and 282,444 crisis-related messages for participant systems to analyze, of which 14,835 COVID-related and 19,784 crisis-related messages have been manually annotated. Analyses of these new datasets and participant systems demonstrate first that both the distributions of information type and priority of information vary between general crises and COVID-19-related discussion. Secondly, despite these differences, results suggest leveraging general crisis data in the COVID-19 context improves performance over baselines. Using these results, we provide guidance on which information types appear most consistent between general crises and COVID-19.
	Address	New Jersey Institute of Technology; University of Glasgow; National Institute of Standards and Technology
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Social Media for Disaster Response and Resilience	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	cbuntain@njit.edu			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2360
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	Author	Congcong Wang; Paul Nulty; David Lillis
	Title	Crisis Domain Adaptation Using Sequence-to-Sequence Transformers			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	655-666
	Keywords	Domain Adaptation, Emergency Response, Social media, Transformers
	Abstract	User-generated content (UGC) on social media can act as a key source of information for emergency responders incrisis situations. However, due to the volume concerned, computational techniques are needed to effectively filter and prioritise this content as it arises during emerging events. In the literature, these techniques are trained using annotated content from previous crises. In this paper, we investigate how this prior knowledge can be best leveraged for new crises by examining the extent to which crisis events of a similar type are more suitable for adaptation tonew events (cross-domain adaptation). Given the recent successes of transformers in various language processing tasks, we propose CAST: an approach for Crisis domain Adaptation leveraging Sequence-to-sequence Transformers. We evaluate CAST using two major crisis-related message classification datasets. Our experiments show that ourCAST-based best run without using any target data achieves the state of the art performance in both in-domain and cross-domain contexts. Moreover, CAST is particularly effective in one-to-one cross-domain adaptation when trained with a larger language model. In many-to-one adaptation where multiple crises are jointly used as the source domain, CAST further improves its performance. In addition, we find that more similar events are more likely to bring better adaptation performance whereas fine-tuning using dissimilar events does not help for adaptation. To aid reproducibility, we open source our code to the community.
	Address	University College Dublin; University College Dublin; University College Dublin
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Social Media for Disaster Response and Resilience	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	wangcongcongcc@gmail.com			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2362
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	Author	Congcong Wang; Paul Nulty; David Lillis
	Title	Transformer-based Multi-task Learning for Disaster Tweet Categorisation			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	705-718
	Keywords	Disaster Response, Tweet Analysis, Transformers, Natural Language Processing
	Abstract	Social media has enabled people to circulate information in a timely fashion, thus motivating people to post messages seeking help during crisis situations. These messages can contribute to the situational awareness of emergency responders, who have a need for them to be categorised according to information types (i.e. the type of aid services the messages are requesting). We introduce a transformer-based multi-task learning (MTL) technique for classifying information types and estimating the priority of these messages. We evaluate the effectiveness of our approach with a variety of metrics by submitting runs to the TREC Incident Streams (IS) track: a research initiative specifically designed for disaster tweet classification and prioritisation. The results demonstrate that our approach achieves competitive performance in most metrics as compared to other participating runs. Subsequently, we find that an ensemble approach combining disparate transformer encoders within our approach helps to improve the overall effectiveness to a significant extent, achieving state-of-the-art performance in almost every metric. We make the code publicly available so that our work can be reproduced and used as a baseline for the community for future work in this domain.
	Address	University College Dublin; University College Dublin; University College Dublin
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Social Media for Disaster Response and Resilience	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	wangcongcongcc@gmail.com			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2366
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	Author	Cornelius Dold; Christopher Munschauer; Ompe Aimé Mudimu
	Title	Real-Life Exercises as a Tool in Security Research and Civil Protection – Options for Data Collections			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	244-250
	Keywords	Real-Life Exercises; Data Collection; Emergency Response; Civil Protection; Large-Scale Exercises
	Abstract	A real-life exercise is a scientific method used by the TH Köln to generate data sets of new technologies and operational concepts derived from research projects. The Institute of Rescue Engineering and Civil Protection (German acronym: IRG) uses a real-time locating system (RTLS), video surveillance, observers and a mass casualty incident benchmark to generate motion profiles, information flows and information on the quality of care. In this practitioner paper these different methods will be discussed and the combination of different data is described. Furthermore, an outlook is given on the extent to which the method will be improved and expand-ed in the future. Concluding it can be said that the combination of all collected data is essential for the evalua-tion of a real-life exercise in security research or civil protection.
	Address	TH Köln – University of Applied Sciences, Cologne; TH Köln – University of Applied Sciences, Cologne; TH Köln – University of Applied Sciences, Cologne
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-24	ISBN	2411-3410	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	cornelius.dold@th-koeln.de			Approved	no
	Call Number				Serial	2225
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	Author	Cossentino, M.; Guastella, D.A.; Lopes, S.; Sabatucci, L.
	Title	Adaptive Execution of Workflows in Emergency Response			Type	Conference Article
	Year	2023	Publication	Proceedings of the 20th International ISCRAM Conference	Abbreviated Journal	Iscram 2023
	Volume		Issue		Pages	784-796
	Keywords	Emergency Management; Disaster Response; Adaptive Workflow Execution; Standard Operating Procedure (SOP)
	Abstract	In emergencies, preparation is of paramount importance but it is not sufficient. As we know, emergency agencies develop extensive (text) plans to deal with accidents that could occur in their territories; their personnel train to enact such procedures, but, despite that, the unpredictable conditions that occur during an emergency require the ability to adapt the plan promptly. This paper deals with the last mile of a process we defined for enabling the adaptive execution of such emergency plans. In previous works, we discussed how to convert a free-text plan into a structured-text form, represent this plan using standard modelling notations, and extract goals that plans prescribe to be fulfilled. In this paper, we propose an approach for executing these plans with a workflow execution engine enriched by the capability to support runtime adaptation.
	Address	National Research Council of Italy (CNR); Machine Learning Group Université Libre de Bruxelles; National Research Council of Italy (CNR); National Research Council of Italy (CNR)
	Corporate Author				Thesis
	Publisher	University of Nebraska at Omaha	Place of Publication	Omaha, USA	Editor	Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi
	Language	English	Summary Language		Original Title
	Series Editor	Hosssein Baharmand	Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition	1
	ISSN		ISBN		Medium
	Track	Applications, Tools, and Components for Crisis Management	Expedition		Conference
	Notes	http://dx.doi.org/10.59297/ZOZS6664			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2566
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	Author	Cruz, J.A. dela; Hendrickx, I.; Larson, M.
	Title	Towards XAI for Information Extraction on Online Media Data for Disaster Risk Management			Type	Conference Article
	Year	2023	Publication	Proceedings of the 20th International ISCRAM Conference	Abbreviated Journal	Iscram 2023
	Volume		Issue		Pages	478-486
	Keywords	Disaster Risk Management; Information Extraction; Explainable AI (XAI); Explainabilit
	Abstract	Disaster risk management practitioners have the responsibility to make decisions at every phase of the disaster risk management cycle: mitigation, preparedness, response and recovery. The decisions they make affect human life. In this paper, we consider the current state of the use of AI in information extraction (IE) for disaster risk management (DRM), which makes it possible to leverage disaster information in social media. We consolidate the challenges and concerns of using AI for DRM into three main areas: limitations of DRM data, limitations of AI modeling and DRM domain-specific concerns, i.e., bias, privacy and security, transparency and accountability, and hype and inflated expectations. Then, we present a systematic discussion of how explainable AI (XAI) can address the challenges and concerns of using AI for IE in DRM.
	Address	Centre for Language Studies, Centre for Language and Speech Technology, Radboud University; Centre for Language Studies, Centre for Language and Speech Technology, Radboud University; Centre for Language Studies,Inst. for Computing and Information Sciences,Radboud University
	Corporate Author				Thesis
	Publisher	University of Nebraska at Omaha	Place of Publication	Omaha, USA	Editor	Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi
	Language	English	Summary Language		Original Title
	Series Editor	Hosssein Baharmand	Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition	1
	ISSN		ISBN		Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes	http://dx.doi.org/10.59297/BHAE3912			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2541
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	Author	Dahlke, D.; Kaiser, S.; Bayer, S.
	Title	Self-Localization: A proposal to equip first responders with a robust and accurate GNSS device			Type	Conference Article
	Year	2023	Publication	Proceedings of the 20th International ISCRAM Conference	Abbreviated Journal	Iscram 2023
	Volume		Issue		Pages	242-251
	Keywords	Self-Localization; GNSS; First Responder Localization; Multi Frequency GNSS; Multi Constellation GNSS
	Abstract	In this paper we explore the GNSS positioning capabilities in the context of search and rescue operations. Our contribution is a tool that robustly receives and precisely evaluates GNSS signals. The final positioning information is then transmitted to an orchestrator where other tools like augmented reality utilities or the command and control have access to. During the time from the project start in September 2021 to December 2022 the components have been chosen, and the design and software of the tool have been developed. Furthermore, some of the tool’s capabilities have been tested and compared during field trials with first responders and measurement campaigns. The developed tool outperforms the commonly used smartphone localization in terms of accuracy, operation time and time to get a GNSS fix. This reliability improvement helps to identify someones position in adverse conditions.
	Address	DLR German Aerospace Center; DLR German Aerospace Center; I.S.A.R. Germany
	Corporate Author				Thesis
	Publisher	University of Nebraska at Omaha	Place of Publication	Omaha, USA	Editor	Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi
	Language	English	Summary Language		Original Title
	Series Editor	Hosssein Baharmand	Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition	1
	ISSN		ISBN		Medium
	Track	Technologies for First Responders	Expedition		Conference
	Notes	http://dx.doi.org/10.59297/QQLO9872			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2522
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	Author	Daniel Lichte; Dustin Witte; Kai-Dietrich Wolf
	Title	Comprehensive Security Hazard Analysis for Transmission Systems			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1145-1153
	Keywords	Physical Security; Energy Transmission Systems; Scenario Analysis; Threat Analysis; Risk Assessment
	Abstract	Critical energy infrastructures are more and more focused upon by politics and society. Modern society depends on these structures, since they enable the steady support of electricity and other types of energy. Deliberately precipitated hazards of certain critical parts of electrical transmission systems (ETS) can lead to catastrophic consequences. Therefore, the analysis of feasible security hazards and resulting consequences for the operation of transmission systems are a concern to transmission system operators (TSO). Alas, there is no common method available that comprehensively identifies these feasible security related scenarios and classifies them according to their overall criticality for the safe operation of the ETS. To tackle this challenge, we propose a comprehensive, yet easy-to-apply method to systematically identify and assess the criticality of security threat scenarios. It is conducted in four steps and consists of a matrix based consistency check of threat scenarios in a defined solution space and a convenient semi-quantitative assessment of a risk factor for the ETS. The approach is illustrated by the simplified generic example of an EETS.
	Address	German Aerospace Center; University of Wuppertal; University of Wuppertal
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-104	ISBN	2411-3490	Medium
	Track	Open Track	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	daniel.lichte@dlr.de			Approved	no
	Call Number				Serial	2305
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	Author	Dario Salza; Edoardo Arnaudo; Giacomo Blanco; Claudio Rossi
	Title	A 'Glocal' Approach for Real-time Emergency Event Detection in Twitter			Type	Conference Article
	Year	2022	Publication	ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2022
	Volume		Issue		Pages	570-583
	Keywords	Emergency; Event Detection; Social Media; Twitter; Incremental Clustering
	Abstract	Social media like Twitter offer not only an unprecedented amount of user-generated content covering developing emergencies but also act as a collector of news produced by heterogeneous sources, including big and small media companies as well as public authorities. However, this volume, velocity, and variety of data constitute the main value and, at the same time, the key challenge to implement and automatic detection and tracking of independent emergency events from the real-time stream of tweets. Leveraging online clustering and considering both textual and geographical features, we propose, implement, and evaluate an algorithm to automatically detect emergency events applying a ‘glocal’ approach, i.e., offering a global coverage while detecting events at local (municipality level) scale.
	Address	LINKS Foundation; LINKS Foundation; LINKS Foundation; LINKS Foundation
	Corporate Author				Thesis
	Publisher		Place of Publication	Tarbes, France	Editor	Rob Grace; Hossein Baharmand
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2411-3387	ISBN	978-82-8427-099-9	Medium
	Track	Social Media for Crisis Management	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2440
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	Author	Dashley K. Rouwendal van Schijndel; Jo E. Hannay; Audun Stolpe
	Title	Simulation Vignette Generation from Answer Set Specifications			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	110-121
	Keywords	Exercise Management; Answer Set Programming; Mixed Reality Simulations; Vignette Generation
	Abstract	We investigate an approach that allows exercise managers to design simulations with an explicit focus on building skills, rather than having to focus on all the objects and interactions that a simulation must have. Exercise managers may design exercises at various levels of abstraction and always independently of how those sessions are implemented in simulations, while simulation components that implement the design are assembled and to some extent, automatically, behind the scenes. We outline (1) how Answer Set Programming can assist exercise managers in exercise planning and (2) how automated stage and content generation may be used to invoke appropriate simulation components to realize the design. For deliberate and recurrent training of decision-making skills, stages and content must vary to avoid familiarity (testing effects). We conclude by distilling a main research hypothesis that stipulates how (1) and (2) represent two modes of automated reasoning (so-called deductive versus abductive) and how that distinction clarifies the planning task.
	Address	University of Oslo, Department of Technology Systems; Norwegian Computing Center, Department of Applied Research in Information Technology; University of Oslo, Department of Technology Systems, Norwegian Computing Center, Department of Applied Research in Information Technology
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-11	ISBN	2411-3397	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	d.k.rouwendal@its.uio.no			Approved	no
	Call Number				Serial	2212
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	Author	Dashley Rouwendal van Schijndel; Audun Stolpe; Jo Erskine Hannay
	Title	Toward an AI-based external scenario event controller for crisis response simulations			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	106-117
	Keywords	Scenario event controller, AI Planning, Modelling and Simulation, Simulation controller
	Abstract	There is a need for tool support for structured planning, execution and analysis of simulation-based training for crisisresponse and management. As a central component of an architecture for such tool support, we outline the design ofan AI-based scenario event controller. The event controller is a component that uses machine reasoning to computethe next state in a scenario, given the actions performed in the corresponding simulation (execution of the scenario).Scenarios are specified in Answer Set Programming, which is a logic programming language we use for automatedplanning of training scenarios. A plan encoding in ASP adds expressivity in scenario specification and enablesmachine reasoning. For exercise managers this gives AI-based tool support for before-action and during-actionreviews to optimize learning. In line with Modelling and Simulation as as Service, our approach externalizes eventcontrol from any particular simulation platform. The scenario, and its unfolding in terms of events, is externalizedas a service. This increases interoperability and enables scenarios to be designed and modified readily and rapidlyto adapt to new training requirements.
	Address	University of Oslo; Norsk Regnesentral; Norsk Regnesentral
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	d.k.rouwendal@its.uio.no			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2318
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	Author	David Wodak; Kenny Meesters
	Title	How To Improve HO/TO's: An Exploratory Study on The Alignment Between Information, Technology And Crisis teams			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	459-470
	Keywords	Crisis handovers, information technology, organizational processes, information quality, crisis teams
	Abstract	In the last decade, the number of crises has increased, and have become more complex. Crisis response does not only focus on rescue operations, or separate stages but rather it is an integrated and continuous process. During this continuous process, several handovers take place. A handover is an important, critical but challenging moment during a crisis, due to the organizational factors that influence the handover and the technology used to transfer information. Since these are crucial elements of a Crisis handover, it would indicate that the alignment between these factors could lead to the improvement of Crisis handovers. However, certain barriers resulted in a lack of alignment. An important barrier originates from the organizational processes. These have a lack of focus on which crisis managers are involved in the handover and thus create a lack of alignment between the systems and information used by various crisis teams.
	Address	Tilburg University; Tilburg University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Enhancing Resilient Response in Inter-organizational Contexts	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	D.wodak@hotmail.com			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2347
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	Author	Debora Robles Perez; Manuel Esteve Domingo; Israel Perez Llopis; Federico J. Carvajal Rodrigo
	Title	System and Architecture of an Adapted Situation Awareness Tool for First Responders			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	928-936
	Keywords	Critical Infrastructure Protection; First Responder; Command and Control; Autonomous Vehicles; Resilience
	Abstract	First responders (FRs) in Europe are currently facing large natural and man-made disasters (e.g. wild fire, terrorist attacks, industrial incidents, big floods, gas leaks etc.), that put their own lives and those of thousands of others at risk. Adapted situation awareneSS tools and taIlored training curricula for increaSing capabiliTies and enhANcing the proteCtion of first respondErs (ASSISTANCE) is an ongoing European H2020 project which main objective is to increase FRs Situation Awareness (SA) for helping and protecting different kinds of FRs' organizations that work together in large scale disasters mitigation. ASSISTANCE will enhance the SA of the FRs organisations during their mitigation activities through the integration of new paradigms, tools and technologies (e.g. drones/robots equipped with a range of sensors, robust communications capabilities, etc.) with the main objective of increasing both their protection and their efficiency.
	Address	Universitat Politècnica de València; Universitat Politècnica de València; Universitat Politècnica de València; Universitat Politècnica de València
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-83	ISBN	2411-3469	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	derobpe@upvnet.upv.es			Approved	no
	Call Number				Serial	2284
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