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Opti-Alert: Enhancing the efficiency of alerting systems through personalized, culturally sensitive multi-channel communication (Opti-Alert)
Start date: Jan 1, 2011, End date: Apr 30, 2014 PROJECT  FINISHED 

The objective of this project proposal is to develop an alerting tool that(a) allows for a rapid simulation of the impact of different alerting strategies (depending on the selected media-mix and current availability of communication media), (b) supports the composition of the optimal mix of communication channels (individualized alerting channels and mass media), (c) improves alert compliance through socio-cultural adaptation and personalization of alert messages and communication channels, (d) supports the rapid and automated implementation of a selected alert strategy, (e) can simultaneously address a plethora of communication channels to facilitate efficient high-throughput alerting, and (f), can be integrated with existing tools and legacy systems via well-defined interfaces.These objectives will be supported by the following key research activities:(a) In-depth analysis of the impact which socio-cultural and regional factors have on risk perception and risk communication, (b) Analysis of the influence which the observed socio-cultural differences have on regional alerting strategies, (c) Analysis of the impact of individualized alerting (via SMS, E-Mail etc.) and alerting via the mass media, (d) Identification of best-practices in alerting via mass media, (e) Definition of appropriate algorithms for the simulation of alert propagation within the population, depending on the selected mix of communication channels.One innovative aspect of this project is to improve the impact of alerts by developing alert strategies which take socio-cultural characteristics of the recipients into account. This can refer both to differences in risk perceptions and different usage patterns with respect to media and communication channels. Based upon the situational and socio-cultural context of an alert situation, the authorities can swiftly simulate different alerting strategies and select the most appropriate one.
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