This article explores the impact of machine learning (ML) and automation systems in improving logistics efficiency in the por t and maritime sector. Through a literature review approach and qualitative analysis, it highlights how these technologies can optimize key operations, reduce costs, and minimize errors in the maritime supply chain. In addition, challenges and opportunities for large-scale implementation are identified. The results indicate that ML and automation-based solutions are essential to meet the growing demands of global trade.

Machine Learning and Automation Systems to Improve Port and Maritime Logistics Efficiency / Zevallos, Juan Carlos Leonardo Nizama; Converso, Giuseppe; Hernández, Alberto Delgado; Doria-Andrade, J.. - In: JOURNAL OF ECOHUMANISM. - ISSN 2752-6801. - 4:1(2025), pp. 625-631. [10.62754/joe.v4i1.5844]

Machine Learning and Automation Systems to Improve Port and Maritime Logistics Efficiency

Converso, Giuseppe;
2025

Abstract

This article explores the impact of machine learning (ML) and automation systems in improving logistics efficiency in the por t and maritime sector. Through a literature review approach and qualitative analysis, it highlights how these technologies can optimize key operations, reduce costs, and minimize errors in the maritime supply chain. In addition, challenges and opportunities for large-scale implementation are identified. The results indicate that ML and automation-based solutions are essential to meet the growing demands of global trade.
2025
Machine Learning and Automation Systems to Improve Port and Maritime Logistics Efficiency / Zevallos, Juan Carlos Leonardo Nizama; Converso, Giuseppe; Hernández, Alberto Delgado; Doria-Andrade, J.. - In: JOURNAL OF ECOHUMANISM. - ISSN 2752-6801. - 4:1(2025), pp. 625-631. [10.62754/joe.v4i1.5844]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/1005340
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