The member states of International Maritime Organization (IMO) have been leading in and enforcing the use of automatic identification systems (AIS) in the analysis of ship-to-ship collisions, vessel monitoring, and maritime traffic management offshore. This study will help non-federal stakeholders understand the AIS data and contribute to future research by assessing difficulties and improving access to data and applications. This study introduces the basics of AIS materials, shared channels, and currently developed applications, and discusses areas where they can be incorporated in the future. The literature revealed that using AIS data will be beneficial to the public as well as to business and public agencies.

Major ports worldwide suffered from various problems such as labor shortage, port congestion, and global supply chain disruptions during COVID-19. To ensure stable operations of ports in such scenarios, one option is to adopt fully automated terminals. This study aimed at evaluating the performance of fully automated terminals compared with that of non-fully automated ones during the disrupted logistics due to coronavirus. Four ports that simultaneously operate both fully and non-fully automated terminals were selected. The performance of the target terminals was measured based on quantitative factors: throughput, number of ship arrivals, and berthing time. The results showed that the fully automated container terminals present better operational performance than the non-fully automated terminals. The former achieved large increments in the throughput, small decreases in the berthing time per ship, and increases in the number of ship arrivals. Moreover, there were economic benefits, revealing that the total terminal profit at the fully automated terminals was significantly increased, whereas that at the non-fully automated ones decreased based on berthing times. Therefore, fully automated terminals can be considered as alternatives for responding flexibly and stably during crises such as COVID-19.