Crack Detection Model in Buildings and Bridges Via Computer Vision Technique with Artificial Intelligence (AI) – Recent Advances, Challenges and Future Direction
Fidelis Nfwan Gonten1, Otene Patience Unekwuojo2
1Fidelis Nfwan Gonten, Admiralty University of Nigeria/Industry, Asaba, Nigeria.
2Otene Patience Unekwuojo, Admiralty University of Nigeria/Industry, Asaba, Nigeria.
Manuscript received on 04 June 2024 | First Revised Manuscript received on 20 June 2025 | Second Revised Manuscript received on 07 July 2025 | Manuscript Accepted on 15 July 2025 | Manuscript published on 30 July 2025 | PP: 25-32 | Volume-12 Issue-7, July 2025 | Retrieval Number: 100.1/ijies.H111012080825 | DOI: 10.35940/ijies.H1110.12070725
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: As the fourth scientific and technological revolution approaches, artificial intelligence (AI) technology is subversively redefining social production and human life. The planning, design, building, maintenance, and management of civil infrastructures have all incorporated it extensively. Within the vision-based community, scientists have focused on utilising deep learning techniques, which are integral to artificial intelligence, to analyse and manage the massive volume of monitoring data. In this study, we evaluate methods for crack detection that have been developed using image processing and Artificial Intelligence. For this purpose, numerous research articles from prestigious conferences and journals were obtained, and the corresponding crack detection methods for the proposed technique were examined, including their features, performance, dataset details, and the specific component to which the process is applicable. The outcome and accompanying constraints of every method are recorded. A comparative analysis of various techniques is carried out to identify the challenges and promising approaches for automatic crack detection in buildings and bridges.
Keywords: Crack Detection, Computer Vision, Artificial Intelligence, Convolutional Neural Network, Image Segmentation in Buildings.
Scope of the Article: Electrical and Electronics