The increasing use of AI components in vehicles and transportation is leading us down a path where the computer makes decisions and we humans have to blindly trust the AI and live with those decisions. Explainable AI is increasingly becoming an area of great interest to various user groups, such as citizens who want to trust the systems they use, legal entities who are responsible for liability and accountability, and researchers who want to understand the limitations of AI and improve the models. The goal of AITHENA is to research and develop methods to create transparency and interpretability of AI models for use in CCAM solutions. 

Further information can be found here.

As part of the project, the digital transformation in industry is also to be driven forward in the highly specialized production environments of the aviation industry with small batch sizes. The aim is to sustainably reduce control and planning efforts in production. State-of-the-art technologies from the field of deep reinforcement learning are used, in which agents learn independently to develop the best approach for a defined planning goal.

Further information can be found here.

The project opens up two perspectives for AR/VR solutions. On the one hand, a solution will be developed, tested and made available that teachers with little IT expertise can use and fill with their own, diverse teaching content. On the other hand, the developed solution will be available as open source, so that researchers and developers from universities in NRW can further develop it for new research and teaching purposes. 

Further information can be found here.

In this project, we design, develop and evaluate AI algorithms for the semi-automated damage assessment of freight cars in train formation. The goal is to bring in the state of the art in the use of artificial intelligence for the localization and classification of defects in image data, to adapt and extend established methods from the academic environment for the present use case.

For more information, please click here.

The objective of the research project is the development, testing and implementation of deep learning methods for inline quality prediction in welding processes as well as the research and development of continual learning methods in order to be able to use the trained models sustainably and efficiently across variations of the process. Based on heterogeneous data from the welding process - including control variables and sensor data - the models will be able to assess the current process condition and perform a quantitative prediction of the expected weld quality. 

Further information can be found here.

The central goal of CC5G.NRW is to contribute to the development of NRW as a lead market for 5G. The focus is on new solutions for companies and authorities in the application of 5G, as well as research into social issues relating to security, social inclusion and sustainability. In this context, innovation potentials and obstacles are identified, systemic competencies are developed and expanded, and potentials of 5G are made accessible.

You can find more information here.

In the Giga For Health project, which emerged from the first round of the 5G.NRW funding competition, a 5G campus network at Düsseldorf University Hospital is being used to test whether and to what extent the fifth generation of mobile communications can be used profitably within medical care, research and teaching.

Further information can be found here.

As part of the BMBF program "Innovations for the Production, Service and Work of Tomorrow", the Institute for Technologies and Management of Digital Transformation (TMDT) will enable craft businesses to explore the potential of the Internet of Things (IoT) for themselves and use it profitably within the three-year project.

Further information can be found here.

Within the framework of the in-house project KoLBi-BK, a quantitative and qualitative profiling of industrial and technical schooling at vocational colleges is to be carried out. The focus of the TMDT is on the design of industrial and technical classes with virtual reality. Student teachers will be taught how to create virtual reality lessons and the development of teaching concepts with virtual reality will be examined.

Further information can be found here.

The upcoming traffic shift confronts the automotive supply industry with comprehensive transformation requirements. Answers for the Bergische Region are being developed by the TrAIBeR.NRW project. The project, led by TMDT/SiKom, was created on the joint initiative of the regional IG Metall branch offices and employers' associations.

Further information can be found here.