Drone-Assisted Image Processing Scheme using Frame-Based Location Identification for Crack and Energy Loss Detection in Building Envelopes

Sukjoon Oh, Suyeon Ham and Seongjin Lee
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Sukjoon Oh: Indoor Air Quality Research Center, Korea Institute of Civil Engineering and Building Technology, Goyang-Si 10223, Korea
Suyeon Ham: Department of Aerospace and Software Engineering, Gyeongsang National University, 501 Jinjudaero, Jinju 52828, Korea
Seongjin Lee: Department of AI Convergence Engineering, Gyeongsang National University, 501 Jinjudaero, Jinju 52828, Korea

Energies, 2021, vol. 14, issue 19, 1-19

Abstract: This paper presents improved methods to detect cracks and thermal leakage in building envelopes using unmanned aerial vehicles (UAV) (i.e., drones) with video camcorders and/or infrared cameras. Three widely used contour detectors of Sobel, Laplacian, and Canny algorithms were compared to find a better solution with low computational overhead. Furthermore, a scheme using frame-based location identification was developed to effectively utilize the existing approach by finding the current location of the drone-assisted image frame. The results showed a simplified drone-assisted scheme along with automation, higher accuracy, and better speed while using lower battery energy. Furthermore, this paper found that the cost-effective drone with the attached equipment generated accurate results without using an expensive drone. The new scheme of this paper will contribute to automated anomaly detection, energy auditing, and commissioning for sustainably built environments.

Keywords: drones; frame-based location identification; contour detection; crack inspection; building thermal leakage detection; energy audit (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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