Abstract
Public alert services is gradually becoming popular in smart cities because this enhances the awareness of the citizen about activities within the city. Such a service also ensures the safety and security of the citizens. However the state of the art lacks in providing real-time alerts in a personalized, context-aware fashion utilizing the combined knowledge about the city, its events and its citizens. In this paper, a solution architecture is presented that uses stream reasoning as its backbone which suits the domain of a public alert system very well. The stream reasoner uses rule-based reasoning and queries. The rules are designed as atomic concepts. A fully functional prototype of the proposed system was developed and tested on data of a smart city. The experimental results support that the proposed methodology is very effective.
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