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Automatic façade modelling using point cloud data for energy-efficient retrofitting

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Abstract

Energy-efficient retrofitting of existing buildings is a key aspect for reaching the proposed energy consumption reduction targets fixed by public authorities in different countries. For this task, the availability of as-built building models is of primary importance for both diagnosis of thermal dispersion and designing of retrofitting. In this paper, we present an automated methodology to derive highly detailed 3D vector models of existing building façades starting from terrestrial laser scanning data. The presented methodology first accomplishes the segmentation of the point cloud of a building façade into its planar elements. Then, starting from the identified planar clusters, façade breaklines are automatically extracted to be used later to generate a 3D vector model. During this final step, some priors on urban scenes like the prevalence of straight lines and orthogonal intersections are exploited to set additional constraints. The final product is a semantically enriched 3D model of the building façade that can be integrated in Building Information Model (BIM) for planned maintenance. Eventually, the integration between derived façade models and infrared thermography (IRT) is presented for energy efficiency evaluation of buildings and detection of thermal anomalies.

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Acknowledgments

This work was supported by the EASEE (Envelope Approach to improve Sustainability and Energy efficiency in Existing multi-storey multi-owner residential buildings) project (ID: FP7-2011-NMP EeB, EeB.NMP.2011-3 ‘Energy saving technologies for buildings envelope retrofitting’). Acknowledgements also go to the National Key Basic 973 Research Program of China (Id 2012CB957702).

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Authors and Affiliations

  1. Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via Ponzio 31, 20133, Milano, Italy

    M. Previtali, L. Barazzetti, R. Brumana, B. Cuca & D. Oreni

  2. Polo Territoriale di Lecco, Politecnico di Milano, Via Marco D’Oggiono 18/A, Lecco, Italy

    F. Roncoroni

  3. College of Surveying and Geo-Informatics, Tongji University, 1239 Siping Road, 200092, Shanghai, People’s Republic of China

    M. Scaioni

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  1. M. Previtali
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  2. L. Barazzetti
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Correspondence to M. Previtali.

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Previtali, M., Barazzetti, L., Brumana, R. et al. Automatic façade modelling using point cloud data for energy-efficient retrofitting. Appl Geomat 6, 95–113 (2014). https://doi.org/10.1007/s12518-014-0129-9

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