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The sensor to decision chain in crisis management
Jürgen Moßgraber
author
Désirée Hilbring
author
Hylke van der Schaaf
author
Philipp Hertweck
author
Efstratios Kontopoulos
author
Panagiotis Mitzias
author
Ioannis Kompatsiaris
author
Stefanos Vrochidis
author
Anastasios Karakostas
author
2018
Rochester Institute of Technology
Rochester, NY (USA)
English
In every disaster and crisis, incident time is the enemy, and getting accurate information about the scope, extent, and impact of the disaster is critical to creating and orchestrating an effective disaster response and recovery effort. Decision Support Systems for disaster and crisis situations need to solve the problem of facilitating the broad variety of sensors available today. This includes the research domain of the Internet of Things and data coming from social media. All this data needs to be aggregated and fused, the semantics of the data needs to be understood and the results must be presented to the decision makers in an accessible way. Furthermore, the interaction and integration with risk and crisis management systems are necessary for a better analysis of the situation and faster reaction times. This paper provides an insight into the sensor to decision chain and proposes solutions and technologies for each step.
Sensors
Internet of Things
Knowledge Base
Ontology Visualization
Decision Support
Early Warning
exported from refbase (http://idl.iscram.org/show.php?record=2148), last updated on Mon, 25 Nov 2019 10:50:57 +0100
text
http://idl.iscram.org/files/juergenmossgraber/2018/2148_JuergenMossgraber_etal2018.pdf
JuergenMossgraber_etal2018
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management
Iscram 2018
Kees Boersma
editor
Brian Tomaszeski
editor
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management
2018
Rochester Institute of Technology
Rochester, NY (USA)
conference publication
754
763
978-0-692-12760-5
2411-3387
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