The Secure Prescriptive Analytics project aims to develop an innovative modeling concept that breaks down complex systems, such as industrial plants, into variable sub-models and represents them through surrogate models. The goal is to create an open-source platform that supports the optimization and integration of these models.
The main objective of the “POWERCAST” project funded by the FFG is to increase the cost and supply efficiency of power grids by predicting and optimizing power loads with AI-supported forecasting models.
The research project QML4Med aims to explore the potential of the promising fusion of Quantum Computing and Machine Learning in the medical context.
The aim of the project is to enable the use of methods from prescriptive analytics & machine learning in our automation projects.
DiTwin revolutionizes road management with digital twin technology for optimized asset management.
The aim of SafeSign is to increase confidence in driver assistance systems.
