Research Projects

There are 5 results.

Klimaneutrale Stadt

10., Rothneusiedl - climate model district Rothneusiedl: Preparation for the planned EU mission "New European Bauhaus"

Rothneusiedl will become a pioneering district for climate protection, climate adaptation and the circular economy. The existing RothNEUsiedl Charter outlines nine principles for making the district climate-friendly and inclusive. The dialogical and integrated process involves various target groups, including the planning and construction industry, future residents and businesses, in order to establish a local building culture at an early stage. NEB working principles are applied in order to support the parallel mission statement process.

Klimaneutrale Stadt

Vitality City - Holistic energy strategies for cities in transition

Energy simulation of any size city (municipalities) based on the data from laser scanning and satellite analysis (Geodata) to obtain dynamical energy demands and available energy resources.

Klimaneutrale Stadt

NEBKritQ - New European Bauhaus Quality Criteria for Sustainable Urban Development

Development of quality criteria and process proposals for sustainable urban development based on the dimensions of the New European Bauhaus (ecological sustainability, aesthetics, social inclusion), which can be used for the evaluation as well as for the project development and application of urban development projects.

Stadt der Zukunft

Green BIM 2. Green Information Modelling and Operation: Transformation of the Green Sector through digitalisation

With the project "Green BIM 2" the technology leap from the previous project "Green BIM" – namely the use of BIM in the field of building greening – is continued for further application fields of landscape planning and the results are transmitted into working practice.

Klimaneutrale Stadt

AI4FM - Artificial Intelligence for Facility Management

AI-based anomaly and fault detection in buildings. Digital twins of buildings with simulation models for testing and optimizing rule-based fault detection methods. Mining of the recorded time-series data from existing Building Management Systems to train Machine Learning models for fault detection.