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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Applying Semantic Web Technologies for Diagnosing Road Traffic Congestions
verfasst von : Freddy Lécué, Anika Schumann, Marco Luca Sbodio
Erschienen in: The Semantic Web – ISWC 2012
Verlag: Springer Berlin Heidelberg
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Diagnosis, or the method to connect causes to its effects, is an important reasoning task for obtaining insight on cities and reaching the concept of sustainable and smarter cities that is envisioned nowadays. This paper, focusing on transportation and its road traffic, presents how road traffic congestions can be detected and diagnosed in quasi real-time. We adapt pure Artificial Intelligence diagnosis techniques to fully exploit knowledge which is captured through relevant semantics-augmented stream and static data from various domains. Our prototype of semantic-aware diagnosis of road traffic congestions, experimented in Dublin Ireland, works efficiently with large, heterogeneous information sources and delivers value-added services to citizens and city managers in quasi real-time.