GAIA-X project GAIA-X 4 KI started at the Institute for Innovative Mobility

Data and Services Ecosystem for AI-Oriented Research & Development

GAIA-X 4 AI focuses on building a GAIA-X-based data and services ecosystem for training and validating automotive-relevant AI-applications.

The mobility of the future is indispensably linked to big data. To further develop this data and the applications associated with it, the GAIA-X 4 KI project started on June 1, 2021. With a total budget of 18 million euros, a consortium of 16 partners, including major industrial partners such as Continental and Intel as well as research institutions such as Fraunhofer ISST and ITWM, is researching how the data required for future mobility can be structured and used. THI is participating through the Institute for Innovative Mobility with a budget of 900,000 euros. The focus is on the functional safety of the electronic systems in the vehicle, without which autonomous driving will not be possible. 

GAIA-X 4KI uses artificial intelligence as technical systems become more sophisticated and sees itself as a central and initial building block of the BMWi-driven initiative to establish a GAIA-X cloud/edge environment for the mobility domain. The GAIA-X 4KI project focuses on the development of a data and service ecosystem for the training and validation of automotive-relevant artificial intelligence applications, because they are essential, for example, for recognizing and interpreting the environment of a vehicle.

This is exemplified in the project for use cases from the context of the automotive industry. Specifically, this involves two interwoven strands with the focus areas of production optimization and automated and connected driving (AVF).

As one of the academic partners, THI contributes to these two use cases. On the one hand, process control applications are being developed using a virtual twin that optimizes complex manufacturing steps based on data available in the GAIA-X ecosystem. Second, THI is contributing to the development of a "monitoring" service within GAIA-X. This will be performed by data-driven condition monitoring algorithms to detect malfunctions before they occur.

Furthermore, GAIA-X 4 AI, as the first of several projects, will initially bring the GAIA-X domain "Mobility" to life and seamlessly integrate into the GAIA-X 4 Future Mobility project family.

In summary, the central contribution of GAIA-X 4 AI lies in the first-time linking of the topics GAIA-X, manufacturing processes and innovative vehicle functions, as well as research on cloud systems and the handling of the associated data and services.