Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/eswc2014/paper/in-use/205> ?p ?o. }
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- 205 creator freddy-lecue.
- 205 creator marco-luca-sbodio.
- 205 creator pierpaolo-tommasi.
- 205 creator robert-tucker.
- 205 creator simone-tallevi-diotallevi.
- 205 creator veli-bicer.
- 205 type InProceedings.
- 205 label "Predicting Severity of Road Traffic Congestion using Semantic Web Technologies".
- 205 sameAs 205.
- 205 abstract "Predictive reasoning, or the problem of estimating future observations given some historical information, is an important inference task for obtaining insight on cities and supporting efficient urban planning. This paper, focusing on transportation, presents how severity of road traffic congestion can be predicted using semanticWeb technologies. In particular we present a system which integrates numerous sensors (exposing heterogenous, exogenous and raw data streams such as weather information, road works, city events or incidents) to improve accuracy and consistency of traffic congestion prediction. Our prototype of semantics-aware prediction, being used and experimented currently by traffic controllers in Dublin City Ireland, works efficiently with real, live and heterogeneous stream data. The experiments have shown accurate and consistent prediction of road traffic conditions, main benefits of the semantic encoding.".
- 205 hasAuthorList authorList.
- 205 isPartOf proceedings.
- 205 keyword "Ontology stream".
- 205 keyword "Predictive reasoning".
- 205 keyword "Semantic cities".
- 205 keyword "Semantic system in use".
- 205 keyword "Traffic congestion".
- 205 title "Predicting Severity of Road Traffic Congestion using Semantic Web Technologies".