Yeongseo Park , Jaehyuk Lee , Kevin Han , Hyungchul Yoon
{"title":"Automated digital transformation for pedestrian suspension bridges using hybrid semantic structure from motion","authors":"Yeongseo Park , Jaehyuk Lee , Kevin Han , Hyungchul Yoon","doi":"10.1016/j.autcon.2025.106232","DOIUrl":null,"url":null,"abstract":"<div><div>Digital transformation is employed to create digital models that reflect the current state of infrastructure. Conventional semantic structure from motion methods effectively generated digital models of bridges segmented by components through semantic segmentation. However, these methods encounter significant challenges in the digital transformation of pedestrian suspension bridges: the inaccurate modeling of cables due to the inherent limitations of raster data in representing cables. To address these issues, this paper proposes a hybrid semantic structure from motion framework for pedestrian suspension bridges by integrating segmented cables in vector format with other raster format data. The performance of the proposed system was validated through full-scale experiments on a pedestrian suspension bridge in South Korea, achieving a 26.49% improvement in accuracy compared to conventional methods. By automating key aspects of digital transformation, the proposed framework is expected to provide solutions for the management of bridge infrastructure, enhancing safety and operational resilience.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"176 ","pages":"Article 106232"},"PeriodicalIF":9.6000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automation in Construction","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0926580525002729","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Digital transformation is employed to create digital models that reflect the current state of infrastructure. Conventional semantic structure from motion methods effectively generated digital models of bridges segmented by components through semantic segmentation. However, these methods encounter significant challenges in the digital transformation of pedestrian suspension bridges: the inaccurate modeling of cables due to the inherent limitations of raster data in representing cables. To address these issues, this paper proposes a hybrid semantic structure from motion framework for pedestrian suspension bridges by integrating segmented cables in vector format with other raster format data. The performance of the proposed system was validated through full-scale experiments on a pedestrian suspension bridge in South Korea, achieving a 26.49% improvement in accuracy compared to conventional methods. By automating key aspects of digital transformation, the proposed framework is expected to provide solutions for the management of bridge infrastructure, enhancing safety and operational resilience.
期刊介绍:
Automation in Construction is an international journal that focuses on publishing original research papers related to the use of Information Technologies in various aspects of the construction industry. The journal covers topics such as design, engineering, construction technologies, and the maintenance and management of constructed facilities.
The scope of Automation in Construction is extensive and covers all stages of the construction life cycle. This includes initial planning and design, construction of the facility, operation and maintenance, as well as the eventual dismantling and recycling of buildings and engineering structures.