Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/69385
Title: Virtual data for maritime security analytics
Authors: Ng, Constance Kai Ling
Keywords: DRNTU::Engineering
Issue Date: 2016
Abstract: The 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.
URI: http://hdl.handle.net/10356/69385
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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