The Future of Independent Living: The GAiST Team from the University of Siegen Presents AI Solutions at the SmartLivingNEXT Conference 2026

The green light for live operations has been given: On May 19, 2026, more than 150 experts from the fields of politics, research, and business gathered at the Forum for Digital Technologies in Berlin for the SmartLivingNEXT conference. The discussion centered on the transition of cross-vendor, federated data spaces from research to practical application. For our Siegen-based project team from the Medical Informatics and Graph-Based Systems (MIGS) working group, led by Prof. Dr. Kai Hahn and Dr. Christian Weber, this was the perfect setting to present the latest milestones of our satellite project GAiST (“Happy Aging with Smart Living Technology”) together with our partners.

Smart Assistance Meets Medical Informatics 

The primary goal of GAiST is to enable older adults to lead safe and self-determined lives in their own homes and to significantly reduce the daily workload of caregivers. As a scientific partner, the University of Siegen focuses intensively on medical data analysis. In the senior living units, our partners OFFIS and escos use Ambient Assisted Living (AAL) sensors to track daily activity patterns, while certified wearables simultaneously record key vital signs (such as heart rate and ECG signals).

The scientific core of the work in Siegen and Oldenburg lies in AI-supported correlation: We are conducting an in-depth investigation into how environmental patterns and vital signs change prior to critical events—such as falls—to enable treating physicians to make more precise, preventive diagnoses.

Live Demonstration in the Federated Data Space At the well-attended demonstrator exhibition in Berlin, we were able to show how these sensitive processes work in practice. The technological foundation is provided by the open and secure architecture of the SmartLivingNEXT Dataspace. With the successful conclusion of the conference, commercialization and everyday operational use are a big step closer. We look forward to seeing the AI systems and semantic architectures developed in the project now being further implemented in practice as part of the strong SmartLivingNEXT consortium.