Since 2014
Operational shipping intelligence through distributed cloud computing
Labour, Employment and Work in New Zealand
View Archive Info| Field | Value | |
| Title |
Operational shipping intelligence through distributed cloud computing
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| Creator |
Cristea, Dragos Sebastian
Moga, Liliana Mihaela Neculita, Mihaela Prentkovskis, Olegas Nor, Khalil Md Mardani, Abbas |
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| Description |
This paper provides a conceptual architecture for a cloud based platform design, that implements continuously data storage and analysis services for large maritime ships, with the purpose to provide valuable insights for maritime transportation business. We do this by first identifying the need on the shipping market for such kind of systems and also the significance and impact of different factors related to shipping business processes. The architecture presented throughout this paper will be defined around some of the most currently used ICT technologies, like Amazon Cloud Services, Sql Server Databases, .NET Platform, Matlab 2016 or javascript visualization libraries. The proposed system makes possible for a maritime company to gain more knowledge for optimizing the efficiency of its operations, to increase its financial benefits and its competitive advantage. The platform architecture was designed to make possible the storage and manipulation of very large datasets, also allowing the possibility of using different data mining techniques for inferring knowledge or to validate already existent models. Ultimately, the developed methodology and the presented outcomes demonstrate a vast potential of creating better technological management systems for the shipping industry, starting from the challenges but also from the huge opportunities this sector can offer.
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| Publisher |
VGTU Press Technika
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| Date |
2017-08-27
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion Peer-reviewed Article |
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| Format |
application/pdf
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| Identifier |
https://journals.vgtu.lt/index.php/JBEM/article/view/1226
10.3846/16111699.2017.1329162 |
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| Source |
Journal of Business Economics and Management; Vol 18 No 4 (2017); 695-725
2029-4433 1611-1699 |
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| Language |
eng
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| Relation |
https://journals.vgtu.lt/index.php/JBEM/article/view/1226/964
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