BMVg, DTEC : SmartShip

SmartShip – Digital Twins for Intelligent Ships and for Ship Fleets

Sea rescue organizations play an important role in civil security. They secure sea routes, clarify emergencies at sea and provide information on the condition of critical infrastructures at sea. Application scenarios and the scope of shipping traffic are becoming increasingly complex. Methods of artificial intelligence (AI) and machine learning (ML) offer solutions for this. Such methods could help users with increasingly difficult ship configurations, optimize search maneuvers between ships or use imaging methods to automatically detect people and objects in the water, even in rough seas. However, there is currently a lack of powerful sensors (e.g. cameras) and, above all, sensor networking. Furthermore, data from different ships are currently not being compared with one another.

In this project, various ships are therefore to be retrofitted with new sensors including a camera system and built-in IT / AI systems as a test platform. Using this collected data, digital twins are to be created for the ships. A digital twin is defined here as a model of a real system that is enriched in the life cycle and is used to analyze and forecast system behavior. In this case, digital twins also allow the very heterogeneous (sensor) information (navigation, weather, cameras, motor, …) to be combined into a uniform, coordinated forecast model. A digital twin for a ship allows e.g. Detect anomalies such as problems early by comparing expected behavior (forecast of the digital twin) with current sensor information. So prototypes for IT-based ships of a new generation are created here.
Another focus is the creation of such digital twins for fleets of ships. This is intended to optimize both the behavior of the fleet (e.g. for search maneuvers or operational planning) and to examine the transferability of knowledge gained from one ship to another. Various AI services such as anomaly detection and fleet optimization are implemented to verify the methods. Using real-time data and intelligent forecasts, bunker costs can be reduced at the fleet level, operating materials can be procured as required and storage can be reduced.

Duration: September 1, 2020 to December 31, 2024

The SmartShip project is funded by the Federal Ministry of Defense (BMVg) in the DTEC funding program.


Letzte Änderung: 9. October 2020