Data-driven underwater technologies and sensor networks are the lifeline of the flourishing digitized Blue Economy of the future.
This use case aims to enable sensor technology to capture a digital twin of the underwater world in real time and develop Gaia-X compatible structures around data acquisition and processing (from edge to cloud). This is done through a feasibility study based on the Ocean Technology Campus of Fraunhofer IGD and through experimentally advancing the Internet of Underwater Things by creating a Gaia-X compliant data environment.
Offshore wind farms are a key to NetZero- Marispace-X develops solutions for collaborative data collection, management, and smart asset handling.
This use case’s goal is to develop data-driven applications and generate trustworthy data spaces for collaboration and efficiency gains of offshore wind farms by collaborative development of tools to map the entire process chain in the collection and analysis of data and by enabling end-users to store, manage and analyze data over the full lifetime of projects (25 years +).
German waters alone contain over 1.6 million tons of old munitions - new smart ways of data analysis and management to tackle the problem are needed.
The use case aims for realizing significant improvements in the analysis and management of data for munitions recovery through new developments in cloud, edge, and fog computing. This includes the transfer of novel intelligent analytics into a secure and scalable cloud environment as well as Gaia-X compliant implementation of federated identity and trust services for the security-critical ordnance domain.
Ocean plants have high CO2 storage capacities - the use case is intended to provide a basis for determining and optimizing the CO2 savings potential of macrophytes.
The goals of the use case are to identify, quantify and optimize the potentials of using CO2 storage capacities of the oceans in the fight against climate change. This is done by establishing novel analysis methods of sensor fusion of optical remote sensing data and underwater acoustic data and through the development of AI-based predictors of optimal macrophyte settlement areas.