An insight into the Application of AI in maritime and Logistics toward Sustainable Transportation

Abstract

This review article looks at the developing field of artificial intelligence and machine learning in maritime and marine environment management. The marine industry is increasingly interested in applying advanced AI and ML technologies to solve sustainability, efficiency, and regulatory compliance issues. This paper examines maritime and marine AI and ML applications using a deep literature review and case study analysis. Modeling ship fuel consumption, which impacts the environment and operating expenses, is a top responsibility. The study demonstrates that ML approaches such as Random Forest and Tweedie models can estimate ship fuel use. Statistical analysis demonstrates that the Random Forest model beats the Tweedie model regarding accuracy and consistency. For the training and testing datasets, the Random Forest model has high R2 values of 0.9997 and 0.9926, indicating a solid match. Low Root Mean Square Error (RMSE) and average absolute relative deviation (AARD) suggest that the model accurately reflects fuel use variability. While still performing well, the Tweedie model has lower R2 values and higher RMSE and AARD values, suggesting reduced accuracy and precision in fuel consumption prediction. These findings provide light on the potential applications of artificial intelligence and machine learning in maritime and marine environment management. Advanced analytics enables decision-makers to analyze fuel consumption patterns better, increase operational efficiency, and decrease environmental impact, thus improving maritime sustainability.

Leveraging Artificial Intelligence to Enhance Port Operation Efficiency

“…Due to its ability to process large amounts of data, predict patterns, and automate decision-making processes, artificial intelligence (AI) is revolutionising port operations [5][6][7]. An exploration of the various applications of AI illustrates the advantages and the obstacles encountered when incorporating it into port operations, which include the integration of technologies such as IoT and blockchain and the refinement of operational procedures to boost efficiency, cut down on turnaround times, and optimise resource usage to lower costs and reduce greenhouse gas (GHG) emissions [8][9][10][11][12]. The use of AI to enhance cargo handling processes can greatly accelerate loading and unloading activities, as shown by its implementation at the Port of Rotterdam for predicting the best container placement on ships [13,14].…”