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Big Data Analytics for Maintaining Transportation Systems
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0003-0734-0959
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. Mechanical Engineering Department, Government College of Engineering and Technology, Jammu, Jammu, India.ORCID iD: 0000-0001-7229-4050
Maintenance Engineering Group, Design, Production and Management Department, University of Twente, Enschede, The Netherlands.
2019 (English)In: Transportation Systems: Managing Performance through Advanced Maintenance Engineering / [ed] Sarbjeet Singh, Alberto Martinetti, Arnab Majumdar, Leo A. M. van Dongen, Springer , 2019, p. 73-91Chapter in book (Other academic)
Abstract [en]

Big Data Analytics (BDA) is becoming a research focus in transportation systems, which can be seen from many projects within the world. By using sensor and Internet of Things (IoT) technology in transportation system, huge amount of data is been generated from different sources. This data can be integrated, analyzed and visualized for efficient and effective decision-making for maintaining transportation systems. The key challenges that exist in managing Big Data are the designing of the systems, which would be able to handle huge amount of data efficiently and effectively and to filter the most significant information from all the collected data. This chapter will draw attention towards the present scenario and future projections of big data in transportation systems. It also presents big data tools and techniques and then presents one brief case study of BDA in each type of transportation system. In this chapter, a broad overview of Big Data definitions, its history, present, and future prospects are briefed. Several tools and technologies especially for transportation are pointed out for maintaining transportation systems. At the end of the chapter, a definitive case studies on each transportation area is demonstrated.

Place, publisher, year, edition, pages
Springer , 2019. p. 73-91
Series
Asset Analytics, ISSN 2522-5162, E-ISSN 2522-5170
Keywords [en]
Big data analytics, Transportation system, Maintenance, Railway, Road, Aviation, Shipping
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-78438DOI: 10.1007/978-981-32-9323-6_6OAI: oai:DiVA.org:ltu-78438DiVA, id: diva2:1422965
Note

ISBN för värdpublikation: 978-981-32-9322-9, 978-981-32-9323-6

Available from: 2020-04-10 Created: 2020-04-10 Last updated: 2020-04-28Bibliographically approved

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Kour, RavdeepThaduri, AdithyaSingh, Sarbjeet

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