ISSN: 2476-2075

Optometry: Open Access
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  • Editorial   
  • Optom Open Access 2023, Vol 8(3): 194
  • DOI: 10.4172/2476-2075.1000194

Automated Damage Assessment for Post-Earthquake Buildings: A Computer Vision and Augmented Reality Approach

Flora Lum*
Computer Architecture and Network Group, School of Computer Science, University of Castilla-La Mancha, Spain
*Corresponding Author : Flora Lum, Computer Architecture and Network Group, School of Computer Science, University of Castilla-La Mancha, Spain, Email: Floralum@tx.uz.com

Received Date: May 02, 2023 / Published Date: May 30, 2023

Abstract

Earthquakes pose a significant threat to the safety and stability of buildings, requiring prompt and accurate assessment of structural damage for effective recovery and reconstruction efforts. This research article investigates the use of computer vision and augmented reality techniques to develop an intelligent system for damage assessment in post-earthquake buildings. By leveraging image processing, deep learning, and augmented reality visualization, this approach aims to provide reliable, automated, and efficient damage assessment, enabling rapid decision-making and prioritization of resources for reconstruction efforts.

The priority to repair the construction after being damaged by an earthquake is to perform an assessment of seismic buildings. The traditional damage assessment method is mainly based on visual inspection, which is highly subjective and has low efficiency. To improve the intelligence of damage assessments for post-earthquake buildings, this paper proposed an assessment method using CV and AR. Firstly, this paper proposed a fusion mechanism for the CV and AR of the assessment method. Secondly, the CNN algorithm and gray value theory are used to determine the damage information of post-earthquake buildings. Then, the damage assessment can be visually displayed according to the damage information. Finally, this paper used a damage assessment case of seismic-reinforced concrete frame beams to verify the feasibility and effectiveness of the proposed assessment method.

Citation: Lum F (2023) Automated Damage Assessment for Post-Earthquake Buildings: A Computer Vision and Augmented Reality Approach. Optom Open Access 8: 194. Doi: 10.4172/2476-2075.1000194

Copyright: © 2023 Lum F. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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