INTELLIFLOW

The project deals with the optimisation of hydraulic networks in buildings and infrastructures. The majority of these networks often have incorrect settings, which leads to oversized components, increased energy consumption and unnecessary costs. The aim is to develop a scalable, AI-supported solution for automated adjustment that does not require cost-intensive manual adjustment work. Forschung Burgenland GmbH is contributing its extensive expertise in the fields of building technology, energy management and AI to ensure a holistic approach. The scientific support in workshops with experts serves the targeted development of the project. Experience in system hydraulics and energy management will be used to analyse and improve hydraulic systems. As part of the practical implementation, real measurement data from demonstration buildings will be collected and support will be provided in selecting and analysing the buildings. As part of experimental studies, a sensor network will be set up to carry out sectoral temperature and volume flow measurements. Battery-operated IoT sensors and soft sensors are used to model conditions that cannot be measured directly. Standardised communication interfaces ensure seamless integration of the measurement data into the client's developed platform.