3D as-is building energy modeling and diagnostics: A review of the state-of-the-art

Yong K. Cho, Youngjib Ham, Mani Golpavar-Fard

Research output: Contribution to journalArticlepeer-review

Abstract

To achieve ambitious cuts in energy consumptions of the building sector, recent efforts have focused on devising methods that can provide accurate representation of the as-is conditions for existing buildings and in turn increase the quality and effectiveness of building retrofits. Today, 3D geometrical models produced by computer vision and laser scanning methods can be used as the basis of energy modeling purposes. Several methods are also introduced to facilitate the diagnostics and measurement of the thermal and other environmental conditions. To this end, this paper extensively reviews the state-of-the-art techniques that can semi-automatically or automatically create as-is geometrical and thermal models for building energy modeling and retrofit assessment purposes. It also provides an overview on the main algorithms used by these methods for representing spatio-thermal point clouds, automatically converting these point clouds into semantic Building Information Models (BIM) in gbXML format for as-is energy modeling purposes, and also contrasting them with expected energy performance models. The underlying formulations and methods for measuring actual thermal resistance of the building assemblies and mapping them into gbXML-based representations are also presented. The most recent works in the IT-driven building automation system (BAS) for energy conservation purposes are also reviewed. Finally, the technology gaps that need to be addressed in future research are identified and discussed.

Original languageEnglish (US)
Pages (from-to)184-195
Number of pages12
JournalAdvanced Engineering Informatics
Volume29
Issue number2
DOIs
StatePublished - Apr 1 2015

Keywords

  • 3D modeling
  • Building diagnostics
  • Laser scanning
  • Structure from motion
  • Thermal infrared imaging

ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence

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