Time estimation in Port Terminals: The Key Role of Automation Revealed by Data Analysis with Deep Learning

Accurate estimation of the time spent by ships in port terminals plays a vital role in operational efficiency. This paper highlights the significant impact of automation through in-depth data analysis with Deep Learning. The study is based on observations of the time spent by ships as a function of their characteristics, integrating the level of terminal automation and the development ranking of the countries where these ports are located. The deep learning model trained can be used to analyze historical and real-time data, identify patterns, and predict time spent in terminal port accurately. The research findings highlight the variables that have the greatest impact on port performance and discuss how managing these variables effectively can optimize port processes and reduce vessel turnaround times. The study also emphasizes the role of automation, and data analytics in making informed decisions for optimizing port terminal delay. The results demonstrate the tangible benefits of automation in seaport operations, offering valuable insights to decision-makers and port managers to enhance operational efficiency and deliver higher quality services. Leveraging automation can unlock opportunities to improve competitiveness, sustainability, and overall operational performance in the dynamic maritime industry.