An approach based on semantic stream reasoning to support decision processes in smart cities

This paper discusses the use of stream reasoning models and techniques to provide a stream reasoning-based architecture to represent, manage and process data streams produced in the Smart City context, to extract useful knowledge for a better understanding of city phenomena and to support the decision making processes in both the city governance and the citizens. The proposed architecture, taking into account the need for processing heterogeneous data/information across several and different domains, is able to sustain decision-making processes deployed at operational, tactical and strategical levels. Such architecture is distributed and adopts a meet-in-the-middle configuration logic that is really effective and scalable in a complex environment like a (smart) city. The applicability of semantic technologies to implement all the aforementioned features is demonstrated by means of a complex case study realized by using a dataset, related to the city of Aarhus, provided by the CityPulse EU Project.