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Ulrich Meissen, & Frank Fuchs-Kittowski. (2014). Towards a reference architecture of crowdsourcing integration in early warning systems. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 334–338). University Park, PA: The Pennsylvania State University.
Abstract: Crowdsourcing has the potential to become a crucial information source in disaster management. In order to become effective as an integrated part of disaster management systems it is important to set the general architectural foundations for such integrations beyond prototypical experiments. This paper discusses general architectural principles of the application of crowdsourcing in Early Warning Systems (EWS). An integrated architecture is proposed to use classical sensor data and crowdsourcing in an EWS solution. Therefore, typical components of crowdsourcing applications are identified and mapped to monitoring subsystems of EWS's. Three main structural variants of applying crowdsourcing in early warning systems along the example of a prototypical extension of two existing large-scale hydro-meteorological warning systems are presented.
Keywords: Disaster prevention; Disasters; Information systems; Management information systems; Alert systems; Architectural principles; Disaster management; Early warning; Early warning systems; Geo-crowdsourcing; Integrated architecture; Reference architecture; Architecture
Ulrich Meissen, & Agnès Voisard. (2008). Increasing the effectiveness of early warning via context-aware alerting. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 431–440). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The effective implementation of early warning is one of the best investments for disaster prevention and mitigation. In the last decade, we have witnessed strong efforts and progress towards better risk detection, monitoring and prediction. However, the best warnings are ineffective if they cannot be distributed in a timely way and targeted to people at risk. With the evolvement of new Information and Communication Technologies, we have new opportunities and face new challenges for improving classical warning processes. Based on our experience and research results from two user-centered hydro-meteorological Early Warning Systems (EWS) we present an approach for context-aware alerting that can increase considerably the effectiveness of warning. Furthermore, we introduce an applied evaluation model for the effectiveness of an EWS.
Keywords: Disaster prevention; Alert systems; Context-awareness; Disaster prevention and mitigations; Early Warning System; Early warning systems; Evaluation modeling; New information and communication technologies; Research results; Information systems
Track: Early Warning Systems