Abstract
To enhance understanding of congestion points at ports and provide visibility into the incoming goods flow into the USA, this study focuses on maritime ports, using the Port of Boston and New York/New Jersey as case studies. Based on the Automatic Information System (AIS) data, we aim to develop predictive models for port congestion status and the Estimated Time of Arrival (ETA) of container ships. Additionally, we analyze historical commodity flow data to forecast future values, weights, volumes and categories based on Harmonized System (HS) codes. Employing quantitative AIS data analysis provides insights into port congestion dynamics and commodity flow trends, indicating the potential to improve the accuracy of ETA, port management and logistics visibility. This study contributes to both theoretical and practical applications in maritime logistics.
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