TY - GEN
T1 - DeepGPR
T2 - 40th International Symposium on Automation and Robotics in Construction, ISARC 2023
AU - Sher, Bilal
AU - Feng, Chen
N1 - Publisher Copyright:
© ISARC 2023. All rights reserved.
PY - 2023
Y1 - 2023
N2 - Conventionally used moisture detection equipment such as infrared scanners and capacitance meters require a trained interpreter to understand moisture issues on rooftops. Additionally, conventional sensors can only provide reliable results in specific environmental conditions. In this paper, we will discuss the various methods used for roof moisture scans and their limitations. We will then provide an in-depth analysis of GPR paired with deep segmentation neural networks for roof moisture scans, including its advantages, limitations, and potential applications. We will also present a case study demonstrating the effectiveness of this approach in detecting moisture damage in a real-world scenario. Our preliminary experiments find that deep neural networks are effective in segmenting GPR radargrams and finding moisture, with particular neural networks more effective than others.
AB - Conventionally used moisture detection equipment such as infrared scanners and capacitance meters require a trained interpreter to understand moisture issues on rooftops. Additionally, conventional sensors can only provide reliable results in specific environmental conditions. In this paper, we will discuss the various methods used for roof moisture scans and their limitations. We will then provide an in-depth analysis of GPR paired with deep segmentation neural networks for roof moisture scans, including its advantages, limitations, and potential applications. We will also present a case study demonstrating the effectiveness of this approach in detecting moisture damage in a real-world scenario. Our preliminary experiments find that deep neural networks are effective in segmenting GPR radargrams and finding moisture, with particular neural networks more effective than others.
KW - building envelope analysis
KW - Ground penetrating radar
KW - moisture detection
KW - rooftop moisture survey
UR - http://www.scopus.com/inward/record.url?scp=85172935362&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85172935362&partnerID=8YFLogxK
U2 - 10.22260/ISARC2023/0075
DO - 10.22260/ISARC2023/0075
M3 - Conference contribution
AN - SCOPUS:85172935362
T3 - Proceedings of the International Symposium on Automation and Robotics in Construction
SP - 561
EP - 568
BT - Proceedings of the 40th International Symposium on Automation and Robotics in Construction, ISARC 2023
A2 - Garcia de Soto, Borja
A2 - Gonzalez, Vicente
A2 - Brilakis, Ioannis
PB - International Association for Automation and Robotics in Construction (IAARC)
Y2 - 5 July 2023 through 7 July 2023
ER -