Point clouds and thermal data fusion for automated gbXML-based building geometry model generation

dc.contributor.advisor Cho, Yong Kwon
dc.contributor.author Wang, Chao
dc.contributor.committeeMember Augenbroe, Godfried
dc.contributor.committeeMember Kahn, Lawrence F.
dc.contributor.committeeMember Gentry, Russell
dc.contributor.committeeMember Vela, Patricio Antonio
dc.contributor.department Civil and Environmental Engineering
dc.date.accessioned 2015-09-21T15:52:27Z
dc.date.available 2015-09-22T05:30:06Z
dc.date.created 2014-08
dc.date.issued 2014-07-01
dc.date.submitted August 2014
dc.date.updated 2015-09-21T15:52:28Z
dc.description.abstract Existing residential and small commercial buildings now represent the greatest opportunity to improve building energy efficiency. Building energy simulation analysis is becoming increasingly important because the analysis results can assist the decision makers to make decisions on improving building energy efficiency and reducing environmental impacts. However, manually measuring as-is conditions of building envelops including geometry and thermal value is still a labor-intensive, costly, and slow process. Thus, the primary objective of this research was to automatically collect and extract the as-is geometry and thermal data of the building envelope components and create a gbXML-based building geometry model. In the proposed methodology, a rapid and low-cost data collection hardware system was designed by integrating 3D laser scanners and an infrared (IR) camera. Secondly, several algorithms were created to automatically recognize various components of building envelope as objects from collected raw data. The extracted 3D semantic geometric model was then automatically saved as an industry standard file format for data interoperability. The feasibility of the proposed method was validated through three case studies. The contributions of this research include 1) a customized low-cost hybrid data collection system development to fuse various data into a thermal point cloud; 2) an automatic method of extracting building envelope components and its geometry data to generate gbXML-based building geometry model. The broader impacts of this research are that it could offer a new way to collect as is building data without impeding occupants’ daily life, and provide an easier way for laypeople to understand the energy performance of their buildings via 3D thermal point cloud visualization.
dc.description.degree Ph.D.
dc.embargo.terms 2015-08-01
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/54008
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Point cloud
dc.subject As-built
dc.subject As-is
dc.subject gbXML
dc.subject Building geometry model
dc.subject Thermal camera
dc.subject LiDAR
dc.subject Laser scanner
dc.title Point clouds and thermal data fusion for automated gbXML-based building geometry model generation
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Cho, Yong Kwon
local.contributor.corporatename School of Civil and Environmental Engineering
local.contributor.corporatename College of Engineering
relation.isAdvisorOfPublication edb06af8-870c-40db-8fc2-f5b417b89165
relation.isOrgUnitOfPublication 88639fad-d3ae-4867-9e7a-7c9e6d2ecc7c
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level Doctoral
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