Multi-modal data analysis for enhanced nautical skill development
Open Access
Article
Conference Proceedings
Authors: Hui Xue, Tae-eun Kim
Abstract: This paper explores the innovative application of multi-modal data analysis for nautical skill development process. By examining the potential of integrating diverse data sources e.g., ship motion, visual, auditory and sensor data, the possibility of obtaining performance insights could be enhanced, and the decision-making processes in complex navigational environments can be made more transparent. The findings from this systematic literature review revealed a significant gap in the current body of knowledge concerning the analysis of multi-modal data in maritime domain. Through a case study on a sailing route involving navigation under a bridge and interactions with two other vessels, we evaluated the potential of a multi-modal data analysis approach to enhance future nautical training. This work aims to catalyse system development and prompt future research endeavours that align with the intersection of multi-modal data analysis and nautical skill advancement.
Keywords: Multi-modal data analysis
DOI: 10.54941/ahfe1005267
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