Data-driven modeling as decision support for energy renovation for single-family home owners
The project will develop a quantitative method that can assess a building energy use and greenhouse gas emissions using building information modeling (BIM) and machine learning algorithms.
The digitized and parameterized properties in BIM used in the design phase to generate scenarios. That information in turn forms the basis for energy performance simulations and environmental assessment databases, which enable evaluations with regard to energy use and greenhouse gas emissions. By processing generated data in a machine learning algorithm it is possible to extract suggestions for alternative constructions.
The results can in turn form the basis for making different types of impact assessments. With developed method, it is possible for designers to identify technical design solutions with the least possible energy use and greenhouse gas emissions.