Abstract
In this paper we summarize the design and the implementation of an ontology-based condition analyzer which performs on-board fault detection and classification for railway rolling stock. Our system is engineered to run on embedded devices that meet stringent railway regulations for on-board deployment and thus it witnesses the feasibility of ontology-based approaches for the implementation of intelligent information systems even in contexts where memory and processing resources come at a premium.
This work has been partially supported by a research contract from Bombardier Transportation Italy. The authors wish to thank Medservice.com for the support provided and, particularly, Lorenzo Nana and Marco De Luca for their collaboration in the implementation of the project.
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De Ambrosi, C., Ghersi, C., Tacchella, A. (2009). An Ontology-Based Condition Analyzer for Fault Classification on Railway Vehicles . In: Chien, BC., Hong, TP., Chen, SM., Ali, M. (eds) Next-Generation Applied Intelligence. IEA/AIE 2009. Lecture Notes in Computer Science(), vol 5579. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02568-6_46
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DOI: https://doi.org/10.1007/978-3-642-02568-6_46
Publisher Name: Springer, Berlin, Heidelberg
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