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Daniel Stein, Barbara Krausz, Jobst Löffler, Robin Marterer, Rolf Bardeli, Jochen Schwenninger, et al. (2012). Enriching an intelligent resource management system with automatic event recognition. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Event recognition systems have high potential to support crisis management 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 management 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. Â© 2012 ISCRAM.
Keywords: Data handling; Information services; Information systems; Natural resources management; Resource allocation; Service oriented architecture (SOA); Abnormal event detections; Automatic speech recognition; Event recognition; Irm; TETRA channel; Management information systems