Fraunhofer-Gesellschaft

How can medical data be analyzed more effectively, documentation processes be handled more efficiently and how can the basis for clinical decision-making be improved? At DMEA 2026, which will be taking place in Berlin from April 21 to 23, the Fraunhofer-Gesellschaft will be presenting technologies for analyzing health-related data that are designed to reduce the burden on medical staff and facilitate data-based applications in research and care. Five institutes will be presenting their latest developments at the joint Fraunhofer booth (Booth D-109, Hall 2.2). These range from AI-assisted symptom analysis and data spaces that allow for health data to be securely shared to assistance systems for medical documentation, data-based decision-making support and solutions for training and evaluating AI models for medical data.

Present systems do not monitor large PV plants on the module level. Yet that is exactly where faults occur, which affect the connection of several solar modules in series, that is, the complete string. Research scientists at the Fraunhofer Institute for Factory Operation and Automation IFF are developing a sensor system together with partners, which provides a detailed view down to the module level, thus detecting all kinds of anomalies, soiling and defects early.

Overfertilization in agriculture weakens crops, endangers drinking water quality and harms the soil. Researchers at the Fraunhofer Institute for Interfacial Engineering and Biotechnology IGB are now developing an alternative fertilizer that is fully biodegradable and only supplies plants with the nutri-ents they actually need, thus preventing overfertilization.

The development of AI models in joint projects yields improved results because multiple companies contribute their data. The situation becomes critical, however, if a partner withdraws and requests the return of its data. With federated unlearning, Fraunhofer researchers and Fujitsu Research have developed a method for precisely removing data from decentralized AI models.