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Railway Assets: A Potential Domain for Big Data Analytics
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-1938-0985
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-4107-0991
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
2015 (English)In: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 53, p. 457-467, article id 53Article in journal (Refereed) Published
Abstract [en]

Two concepts currently at the leading edge of todays information technology revolution are Analytics and Big Data. The public transportation industry has been at the forefront in utilizing and implementing Analytics and Big Data, from ridership forecasting to transit operations Rail transit systems have been especially involved with these IT concepts, and tend to be especially amenable to the advantages of Analytics and Big Data because they are generally closed systems that involve sophisticated processing of large volumes of data. The more that public transportation professionals and decision makers understand the role of Analytics and Big Data in their industry in perspective, the more effectively they will be able to utilize its promise. This paper gives an overview of Big Data technologies in context of transportation with specific to Railways. This paper also gives an insight on how the existing data modules from the transport authority combines Big Data and how can be incorporated in providing maintenance decision making.

Place, publisher, year, edition, pages
2015. Vol. 53, p. 457-467, article id 53
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-32704DOI: 10.1016/j.procs.2015.07.323ISI: 000360311000052Scopus ID: 2-s2.0-84939150889Local ID: 746f2d23-86f2-4f29-80bd-8b02beed911aOAI: oai:DiVA.org:ltu-32704DiVA, id: diva2:1005938
Conference
INNS Conference on Big Data 2015 : 08/08/2015 - 10/08/2015
Note
Validerad; 2015; Nivå 1; 20150821 (aditha); Konferensartikel i tidskriftAvailable from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-07-10Bibliographically approved

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Publisher's full textScopushttp://www.sciencedirect.com/science/article/pii/S1877050915018268

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Thaduri, AdithyaGalar, DiegoKumar, Uday

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