A Year of Innovation in AI and Digital Twinning for EGI Coordinated Projects interTwin and iMagine

At the end of 2023, interTwin and iMagine, the two running EGI Flagship projects, successfully completed one year of operations. We are happy to share that the project funder, the European Commission, has positively reviewed both projects - allowing them to continue in the same spirit. 

In interTwin, EGI leads a large consortium in developing an interdisciplinary Digital Twin Engine, an open source platform that provides generic and tailored software components for modelling and simulation Digital Twins (DTs). The ambition of the project is to develop a common approach to the implementation of DTs that is applicable across the whole spectrum of scientific disciplines and beyond to facilitate development and collaboration.

iMagine relies on the technical and scientific expertise of the project partners to foster the development of the iMagine AI platform, leveraging the experience of colleagues deeply involved in AI-related projects such as AI4EOSC. The platform gives researchers in aquatic sciences open access to a diverse portfolio of AI-based image analysis services and image repositories from multiple RIs. Eight use cases (and more to come after the iMagine open call!) are testing and improving the platform so that other researchers can benefit from their AI and ML models and tools. 

Andrea Manzi, Technical Coordinator of interTwin, says: ‘The good outcome of the interTwin first EC review meeting has shown the excellent collaborative work of the consortium in co-designing and developing the first version of the project Digital Twin Engine. We are looking forward to a second year of the project focused on component integration and the first version of the Digital Twins to be made available.’ 

Gergely Sipos, iMagine Technical Coordinator, comments: ‘So far, iMagine has demonstrated its pivotal role in providing an effective AI operating platform for marine and freshwater sciences researchers. The various use cases in the project are making notable progress, highlighting the positive impact of AI on image analysis and object recognition in their research projects, leading to faster and more accurate extraction of knowledge from optical images.’

We want to extend our thanks to all project partners in both projects for their commitment to making these projects successful, and we look forward to the upcoming challenges!