Suchergebnisse
FlexHP - AI-supported control models for optimising the flexibility of heat pumps to reduce the load on the electricity grid
Development of a new type of energy management system for heat pumps that enables methods for intelligent heat pump operation and thus maximises flexibility. This requires forecast-based models for control that utilise technologies such as machine learning.
MokiG: Monitoring for climate-neutral buildings
The aim is to develop and implement an innovative monitoring concept to demonstrate the achievement of climate neutrality in buildings. A central element here is the integration and linking of various data sources. The basis for this is a data mesh structure, artificial intelligence and the creation of digital twins. Finally, the methodology will be tested on real buildings and discussed with users.
GreenFDT – Green Façade Digital Twin
In an interdisciplinary framework, the possibilities for optimizing the rear ventilation distance of façade greening elements and their potential impact on indoor and urban climate are being investigated. The precise and comprehensive investigation of these relationships is made possible by the extensive deployment of sensors and measuring tools and furthermore the development and integration of a digital twin in a BIM model.
OctoAI: The next generation of high-performance edge AI for smart buildings
Current IoT (Internet of Things) solutions for buildings depend almost exclusively on cloud infrastructure and cloud-based services. In the OctoAI project, we are developing the next generation of high-performance Edge AI (Artificial Intelligence) for smart buildings. In OctoAI, we combine the concept of edge AI with user-centric energy services and test two edge-ready applications.
Beyond - Virtual Reality enabled energy services for smart energy systems
The Beyond project addressed two different energy services through the interaction of various technologies: state-of-the-art virtual reality (VR), the Internet of Things (IoT), energy simulation and machine learning (ML). Energy service 1 immerses VR users in energy-efficient and sustainable building design through an educational VR game, while energy service 2 improves the maintenance of building systems, particularly heating, ventilation and air conditioning (HVAC) systems, through the application of ML models for predictive maintenance.
BIMpeco - Environmentally relevant product data in collaborative BIM environments
Construction products can pose a risk to the environment and health due to their pollutant content or releases. In the BIMpeco project, workflows and data structures for digital information management of this environmentally relevant product data are developed. For this purpose, the new ISO standards ISO 23387 and ISO 19650-1 are tested and synchronized with established process flows. The project results will be made available on an open-source basis and can be integrated into any Common Data Environment (CDE) that complies with the standards mentioned. The BIMpeco project is the first to lay the foundations for product information management of environmentally relevant properties in the CDE, covering the entire lifecycle and supply chain.