Animation of a simulation model for marine traffic in Singapore waters

• Main Author: Han, Xiao
• Other Authors: Huang Shell Ying
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2023
• Subjects: Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/165863
• Institution: Nanyang Technological University

The animation of marine traffic in Singapore waters is a project aimed at studying vessel behavior using animation methods. Singapore is a global hub for the maritime industry, and studying ship routes is crucial for optimizing ship use, improving fuel efficiency, reducing carbon emissions, and minimizing transportation time and distance while avoiding high-risk areas. Additionally, managing port congestion and infrastructure use, and informing policy decisions regarding trade, transportation, and environmental regulations are additional benefits of studying ship routes. The project involves two main components: data analysis and data cleaning of a dataset of marine vessels and the creation of an animation and visualisation of the refined dataset. The first challenge was to process the TXT file dataset given, which required converting it to a suitable format for the animation platform used. The second challenge was choosing an appropriate animation platform that is free of charge, able to process data with coordinates, and allows customisation of map markers. The data processing and cleaning phase involved converting the dataset to geojson format to ensure that the data is ready to be processed by the animation platform. The animation was then created by using a specialised map software to plot the data points on the map, customising the colour of the vessel routes based on their size, and displaying timestamps. The animation was looped to show the movement of vessels at different time frames. The results of the project showed the movement patterns of vessels in Singapore waters, and it can be used to draw conclusions about vessel behavior. The findings can be applied to marine traffic in other parts of the world, not limited to Singapore. Future improvements include incorporating real-time data, enhancing the visualization with additional data layers, and exploring the use of machine learning techniques for vessel behavior analysis. Overall, this project contributes to the sustainable and efficient operation of the maritime industry.