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

Authors: Daniela Cabiddu; Michela Mortara; Chiara Romanengo; Andreas Scalas; Alice Bellazzi; Lorenzo Belussi; Ludovico Danza; +1 Authors

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

Abstract

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.

Country
Italy
Keywords

urban intelligence, urban mapping, semantic enrichment, energy efficiency, geometric layer

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Related to Research communities
Energy Research