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Using Existing Data to Support Operational Emergency Response in Germany – Current Use Cases, Opportunities and Challenges
Lennart Landsberg
David Ganske
Christopher Munschauer
Ompe Aimé Mudimu
Amanda Hughes
Fiona McNeill
Christopher W. Zobel
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.
urn:ISBN:2411-3425
openurl:?ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Fidl.iscram.org%2F&genre=proceeding&title=Using%20Existing%20Data%20to%20Support%20Operational%20Emergency%20Response%20in%20Germany%20-%20Current%20Use%20Cases%2C%20Opportunities%20and%20Challenges&stitle=Iscram%202020&issn=978-1-949373-27-39&isbn=2411-3425&date=2020&spage=406&epage=415&aulast=Lennart%20Landsberg&au=David%20Ganske&au=Christopher%20Munschauer&au=Ompe%20Aim%E9%20Mudimu&pub=Virginia%20Tech&place=Blacksburg%2C%20VA%20%28USA%29&sid=refbase%3AISCRAM
url:http://idl.iscram.org/show.php?record=2240
citekey:LennartLandsberg_etal2020
citation:Lennart Landsberg, David Ganske, Christopher Munschauer, & Ompe Aimé Mudimu. (2020). Using Existing Data to Support Operational Emergency Response in Germany – Current Use Cases, Opportunities and Challenges. 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. 406-415). Blacksburg, VA (USA): Virginia Tech.
2020
ConferencePaper
text
Emergency Response
Data Analytics
Artificial Intelligence (AI)
Dispatch Strategies
Resilience
file:http://idl.iscram.org/files/lennartlandsberg/2020/2240_LennartLandsberg_etal2020.pdf
Virginia Tech
English
978-1-949373-27-39
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management
2020
406
415
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