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An Integrative APP Producing an Optimal Path for the Vessel in Order to Reduce the Impacts of Cargo Ships on the Environment

Authors

Chenyu Zuo1, Yu Sun2, 1Sage Hill School, USA, 2California State Polytechnic University, USA

Abstract

Almost every business in the world relies in some way on the shipping industry, whether it is to ship goods or natural resources, the shipping industry is undeniably the global industry, However, these very ships that drive the economy also produce close to 1 billion metric tons of carbon dioxide per year. In this project, we explore the use of machine learning to improve the performance of cargo ships in the ocean by implementing a genetic algorithm AI and a virtual simulation environment. An app was made based on using the training developed by the AI to be able to be deployed on cargo ships as part of their navigation system. Once sufficient data regarding a vessel’s environment was collected, the algorithm could then produce an optimal path for the vessel. Experiments show that the AI system could sufficiently adjust to varying conditions and produce optimal paths for vessels.

Keywords

Machine Learning, AI, Mobile APP, environment.

Full Text  Volume 13, Number 4