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Enriching an intelligent resource management system with automatic event recognition

: Stein, Daniel; Krausz, Barbara; Löffler, Jobst; Marterer, Robin; Bardeli, Rolf; Schwenninger, Jochen; Usabaev, Bela

Preprint urn:nbn:de:0011-n-2250797 (786 KByte PDF)
MD5 Fingerprint: 2a28d491c0e589ce2a214afdd9604ae7
Erstellt am: 17.1.2013

Rothkrantz, L. ; Environmental Systems Research Institute -ESRI-:
ISCRAM 2012, 9th International Conference on Information Systems for Crisis Response and Management. Proceedings : Vancouver, Canada, April 2012
Vancouver: Simon Fraser University, 2012
ISBN: 978-0-86491-332-6
5 S.
International Conference on Information Systems for Crisis Response and Management (ISCRAM) <9, 2012, Vancouver>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAIS ()
, event-driven service-oriented architecture, IRM; abnormal event detection; automatic speech recognition; TETRA channel; event-driven service-oriented architecture; event recognition system

Event recognition systems have high potential to support crisis anagement and emergency response. Given the vast amount of possible input channels, automatic processing of raw data is crucial. In this paper, we describe several components integrated in an overall intelligent resource anagement system, namely abnormal event detection in audio and video material, as well as automatic speech recognition within a public safety network. We elaborate on the challenges expected from real life data and the solutions that we applied. The overall system, based on Event-Driven Service-Oriented Architecture, has been implemented and partly integrated into the end users infrastructures. The system is continuously running since almost two years, collecting data for research purposes.