dc.contributor.authorNg, Constance Kai Ling
dc.description.abstractThe increasing number of vessels in an area increases the complexity of the traffic flow for the vessels as well as the large number of collectible data for the maritime industry. Moreover, each vessel has its unique characteristics (microscopic aspect) and the movement is also subjected to the unpredictability of the weather (macroscopic aspect). Therefore, there is a need to be able to predict the vessel’s movements in order to plan intricate shipping lanes that can cater to the various aspects of the vessels and their movements. In this project, a mesoscopic model has been created to interpolate and recreate trajectories from the real time data provided by Thales Solutions Asia Pte Ltd. The model takes into consideration the vessel movements and the characteristics of the vessels to generate a pattern which demonstrates the behavior of the ships. An algorithm will then be applied to visualize the trajectories by means of clustering in order to determine the suitability of the simulation model.en_US
dc.format.extent53 p.en_US
dc.rightsNanyang Technological University
dc.titleVirtual data for maritime security analyticsen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorA S Madhukumaren_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
dc.contributor.organizationThales Asia Pte Ltden_US
dc.contributor.supervisor2Justin Dauwelsen_US

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