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. (Journal of Ecohumanism, 2025)
This article explores the impact of machine learning (ML) and automation systems in improving logistics efficiency in the port 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.