The transportation and development systems in the oceans are becoming more complicated due to emerging novel requirements with autonomy and decarbonization. Severe wave and wind occur more frequently due to climate change. These increase the uncertainty and make operation difficult. As a way to reduce the uncertainty and support the operation, the digital twin is attracting attention in various industries.
The digital twin is a technology that uses AI and data assimilation technologies to create a twin-like model in cyberspace based on information obtained from “objects” in real space through IoT . The digital twin enables us to know the current condition and predict the future more accurately , thus enabling safer and more efficient decision-making. In this research, we aim to realize the digital twin of equipment and structures related to marine transportation and offshore development, such as ships and offshore wind turbines. We are working on the research of monitoring technology using sensors, condition estimation technology using data assimilation methods. We are also developing integrated Ship Analysis System (i-SAS), which is a platform for realizing digital twin systems.
Department of Ocean Technology, Policy, and Environment
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