Enhancing Ship Safety During Mooring Operations on The Basis of Expanded Parameters and Leveraging AI for Real-Time Risk Assessment

Abstract

This paper presents an innovative approach to improve the safety of ship mooring operations by applying an advanced risk assessment model that utilizes Bayesian networks and real-time data processing. The proposed system expands the number of risk parameters considered, including wind speed, current speed and crew fatigue, and utilizes artificial intelligence (AI) to dynamically update risk levels. The system is an end-to-end solution that integrates multiple data sources to provide continuous risk monitoring, reduce human error and improve decision-making during mooring operations. Case studies demonstrate significant reductions in critical incidents and overall operational risk.