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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 (down) 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 Lennart Landsberg; David Ganske; Christopher Munschauer; Ompe Aimé Mudimu
Title Using Existing Data to Support Operational Emergency Response in Germany – Current Use Cases, Opportunities and Challenges Type Conference Article
Year (down) 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020
Volume Issue Pages 406-415
Keywords Emergency Response; Data Analytics; Artificial Intelligence (AI); Dispatch Strategies; Resilience
Abstract The availability of resources in the fire and ambulance services in Germany is facing a radical change. Demographic and social transition is reducing the availability of volunteer personnel, and increasing traffic congestion in cities is resulting in longer travel times for emergency vehicles. This paper presents the findings of the definition phase of a research project that addresses these changes. It shows the basic idea of how resilience of fire and ambulance services can be improved by analyzing operational data from past incidents using artificial intelligence (AI). The primary objective is the development of a decision support system for control center dispatchers, which ensures optimal use of available resources. As the result of the definition phase, this paper gives an overview of existing data, current as well as future use cases and also highlights risks and challenges that have to be considered.
Address TH Köln; TH Köln; TH Köln; TH Köln
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 978-1-949373-27-39 ISBN 2411-3425 Medium
Track Data and Resilience: Opportunities and Challenges Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management
Notes lennart_walter.landsberg@th-koeln.de Approved no
Call Number Serial 2240
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