This research develops a big data-based CS model for maritime traffic assessment, motivated by global shipping growth, the impact of COVID-19, changes in consumer culture, and Industry 4.0 expansion in maritime sectors. Maritime traffic, crucial for g...
This research develops a big data-based CS model for maritime traffic assessment, motivated by global shipping growth, the impact of COVID-19, changes in consumer culture, and Industry 4.0 expansion in maritime sectors. Maritime traffic, crucial for global trade, demands effective management for safety and efficiency. This study aims to quantitatively and objectively evaluate maritime traffic smoothness by analyzing ship operation data. The CS model focuses on unique maritime characteristics, leveraging big data to enhance traffic management solutions and safety. The research methodology includes analyzing domestic and international trends and data to reflect maritime spatiality and continuity. The model's efficacy is tested through case studies on major port routes, comparing it with existing models to suggest improvements. This new approach provides a framework for optimizing maritime traffic routes and supports autonomous, unmanned, and smart ship operations, setting a new paradigm for maritime traffic management.