3D FEATURE RECOGNITION FOR THE ASSESSMENT OF BUILDINGS' ENERGY EFFICIENCY

The real assets, procedures, systems,and subsystems of a city can be virtually represented throughan urban digital twin(DT),which integrates heterogeneous data to learn and evolve with the physical city,offering support to monitor the current status and predict possible future scenarios.A DT of a city can be organized into layers, which represent specific facets of the city and cooperate to address specifici ssues.In this work,we present an application scenario in which a geometric layer,representing the 3D morphology of the urbane nvironment, cooperates with an energy consumption layer,providing knowledge of the peculiarities of thebuilding urban area and in particular of the built fabric,to assess their impact in terms of energy efficiency.The analysis of the urban geometries provides quantitative measuresas useful input,for instance,to define heat leakage.