The DecarbonAIte project aims to extract data on building characteristics from public databases. Use this information to elaborate and reinforce urban digital twin models. Finally, through this platform, to propose optimal renovation measures. The system to be implemented targets various stakeholders, from building owners to policy makers.

Urban modelling and planning tool for energy and invisible environmental factors using AI methods

To plan, build or renovate cities, engineers and decision makers need tools and workflows that are compartmentalized and work ad-hoc without correlating different parameters. To tackle these problems and enable environmental assessment and policy analysis, this project aims to create an urban modeling planning tool for the energy demand of buildings and the invisible environmental factors of noise and wind. The project will . * provide a basis for scenario analysis of any urban area in Sweden. * use AI/ML to enrich existing models . * make the toolsets readily available, and. * enable improved visualization and communication or results.