ABSTRACT
Over the last decade, there has been an important growing trend towards the use of technology to perform building inspections within the Architecture, Engineering and Construction (AEC) industry. To date however, not enough research has been developed to explore durability approach diagnostic inspection. This paper describes the design and implementation of a framework using Close-Range Red-Green-Blue bands (RGB) Photogrammetry based on remote piloted aircraft systems (RPAS) surveying and Laser Scanning for durability failure detection and inspection in concrete buildings. The RPAS utilizes the CRP approach to capture a series of images while Laser Scanning complement the inspection thought the 3D model. The detection approach uses Deep Learning (DL) to classify durability failures in the structure using MATLAB. Finally, the performance of the proposed framework was tested in a case study in Mexico and a comprehensive discussion was presented to highlight the main findings, challenges and opportunities.
