Date of Award

Spring 4-16-2020

Semester of Degree


Document Type

Open Access Thesis

Degree Name

M.S. in Forest and Natural Resources Management


Forest and Natural Resources Management

Major Professor


Steering Committee Member

Dr. Mohamad Razkenari

Steering Committee Member

Dr. Endong Wang


Existing buildings account for 40% of global energy consumption, and two-thirds of them will be still be operational in 2050. As most of these buildings lack the needed documentation for energy upgrades, it is essential to understand and represent the current conditions of their envelopes and mechanical systems. This project proposed a skeleton-based application for reconstructing and classifying pipes in existing buildings using point clouds from laser scanners and thermal images for Building Information Modeling (BIM) applications. MATLAB and Dynamo were used to process and model this information in Revit. Initial results indicate that the application is robust to identifying pipes and connections, and that thermal images can be used to create sematic-rich models. These results can contribute to improving the capabilities of some of the commercially available software for pipe reconstruction in BIM and to expediting the digital reconstruction processes in existing buildings.