Retrofitting existing buildings is a key aspect for reaching the proposed energy consumption reduction targets in all countries. The availability of as-built building model is of primary importance for both thermal lack diagnosis and planning retrofitting works. In particular, integration between Building Information Models (BIMs) and Infrared Thermography (IRT) can be a powerful tool for evaluating building thermal efficiency. Indeed, thermography can be efficiently used to detect thermal bridges and heat losses. However, thermographic images does not allow geometrical measurements whereas precise localization of thermal defects is a main aspect for retrofitting intervention planning. For this reason building models can be efficiently integrated with thermal images and provide metric information to thermographic analysis. In this paper a methodology for combining thermographies, acquired by different platforms, and building models automatically derived from laser scanning technology is presented.
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Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via Ponzio 31, 20133, Milano, Italy
Mattia Previtali & Luigi Barazzetti
Polo Territoriale di Lecco, Politecnico di Milano, Via Marco D’Oggiono 18/A, Lecco, Italy
Fabio Roncoroni
L-I.S.U.T. - D.A.P.I.t. Facoltà Ingegneria, Università degli Studi della Basilicata, Viale dell’Ateneo Lucano, 10, 85100, Potenza, Italy
Beniamino Murgante
Covenant University, Canaanland, Ota, Nigeria
Sanjay Misra
Partimento di Scienze e Tecnologie per LAgricoltura, le Foreste, la Natura e lEnergia, Università degli Studi della Tuscia, Via S. Camillo de Lellis, snc, 01100, Viterbo, Italy
Maurizio Carlini
Dipartimento di Scienze dell’Ingegneria Civile e dell’Architecttura, Politecnico di Bari, Via Orabona, 4, 70125, Bari, Italy
Carmelo M. Torre
International University VNU-HCM, Quarter 6, Linh Trung, Thu Duc, Ho Chi Minh City, Vietnam
Hong-Quang Nguyen
School of Business Systems, Monash University, 3800, Clayton, VIC, Australia
David Taniar
Department of Intelligent Informatics, Kyushu Sangyo University, 2-3-1 Matsukadai, 813-8503, Higashi-ku, Fukuoka, Japan
Bernady O. Apduhan
Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli, 1, 06123, Perugia, Italy
Osvaldo Gervasi
© 2013 Springer-Verlag Berlin Heidelberg
About this paper Cite this paperPrevitali, M., Barazzetti, L., Roncoroni, F. (2013). Spatial Data Management for Energy Efficient Envelope Retrofitting. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2013. ICCSA 2013. Lecture Notes in Computer Science, vol 7971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39637-3_48
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39636-6
Online ISBN: 978-3-642-39637-3
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