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dc.contributor.authorCristea, Dragos Sebastian
dc.contributor.authorMoga, Liliana Mihaela
dc.contributor.authorNeculita, Mihaela
dc.contributor.authorPrentkovskis, Olegas
dc.contributor.authorMd Nor, Khalil
dc.contributor.authorMardani, Abbas
dc.date.accessioned2023-09-18T16:55:45Z
dc.date.available2023-09-18T16:55:45Z
dc.date.issued2017
dc.identifier.issn1611-1699
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/118245
dc.description.abstractThis 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.eng
dc.formatPDF
dc.format.extentp. 695-725
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyCentral & Eastern European Academic Source (CEEAS)
dc.relation.isreferencedbyBusiness Source Complete
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbySocial Sciences Citation Index (Web of Science)
dc.source.urihttp://dx.doi.org/10.3846/16111699.2017.1329162
dc.subjectTD04 - Transporto ir logistikos technologijos, transporto rūšių sąveika / Transport and logistics technology, interaction of transport modes
dc.titleOperational shipping intelligence through distributed cloud computing
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.references54
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionDunarea de Jos University of Galati
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionUniversity of Technology Malaysia
dc.contributor.facultyTransporto inžinerijos fakultetas / Faculty of Transport Engineering
dc.subject.researchfieldT 003 - Transporto inžinerija / Transport engineering
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.enTransportation
dc.subject.enBusiness
dc.subject.enCloud computing
dc.subject.enCompetence
dc.subject.enShip
dc.subject.enMaritime company
dc.subject.enAutomatic ship performance analysis
dcterms.sourcetitleJournal of business economics and management
dc.description.issueiss. 4
dc.description.volumevol. 18
dc.publisher.nameTechnika; Taylor & Francis
dc.publisher.cityVilnius; Londonas
dc.identifier.doi000408730100008
dc.identifier.doi10.3846/16111699.2017.1329162
dc.identifier.elaba23466727


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