{"title":"利用 iPhone LiDAR 相机数据的图像颜色分析,对地下管道安装现场进行自动进度监测,从而提高施工现场效率","authors":"","doi":"10.1016/j.dibe.2024.100557","DOIUrl":null,"url":null,"abstract":"<div><div>This study presents an innovative method utilizing smartphone for automated progress monitoring at underground pipe installation sites. Leveraging the LiDAR iPhone camera, the method captures detailed point cloud data of construction sites. Sophisticated color analysis of images accurately distinguishes between areas with and without pipes within excavations. Key aspects of the proposed workflow include segmentation of the excavation area, differentiation between main and side excavations, and application of an earth color mask in the RGB space to isolate pipes. The research focuses on enhancing measurement precision for excavation width, depth, and pipe burial depth, significantly reducing the manual labor traditionally required at construction sites, thereby offering an efficient and cost-effective solution. We further demonstrated the robustness of the proposed algorithm by applying it to two types of data acquired at actual construction sites. This approach is expected to contribute significantly to the digital transformation in the construction industry.</div></div>","PeriodicalId":34137,"journal":{"name":"Developments in the Built Environment","volume":null,"pages":null},"PeriodicalIF":6.2000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving construction site efficiency through automated progress monitoring of underground pipe installation sites using image color analysis of iPhone LiDAR camera data\",\"authors\":\"\",\"doi\":\"10.1016/j.dibe.2024.100557\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study presents an innovative method utilizing smartphone for automated progress monitoring at underground pipe installation sites. Leveraging the LiDAR iPhone camera, the method captures detailed point cloud data of construction sites. Sophisticated color analysis of images accurately distinguishes between areas with and without pipes within excavations. Key aspects of the proposed workflow include segmentation of the excavation area, differentiation between main and side excavations, and application of an earth color mask in the RGB space to isolate pipes. The research focuses on enhancing measurement precision for excavation width, depth, and pipe burial depth, significantly reducing the manual labor traditionally required at construction sites, thereby offering an efficient and cost-effective solution. We further demonstrated the robustness of the proposed algorithm by applying it to two types of data acquired at actual construction sites. This approach is expected to contribute significantly to the digital transformation in the construction industry.</div></div>\",\"PeriodicalId\":34137,\"journal\":{\"name\":\"Developments in the Built Environment\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2024-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Developments in the Built Environment\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666165924002382\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Developments in the Built Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666165924002382","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
Improving construction site efficiency through automated progress monitoring of underground pipe installation sites using image color analysis of iPhone LiDAR camera data
This study presents an innovative method utilizing smartphone for automated progress monitoring at underground pipe installation sites. Leveraging the LiDAR iPhone camera, the method captures detailed point cloud data of construction sites. Sophisticated color analysis of images accurately distinguishes between areas with and without pipes within excavations. Key aspects of the proposed workflow include segmentation of the excavation area, differentiation between main and side excavations, and application of an earth color mask in the RGB space to isolate pipes. The research focuses on enhancing measurement precision for excavation width, depth, and pipe burial depth, significantly reducing the manual labor traditionally required at construction sites, thereby offering an efficient and cost-effective solution. We further demonstrated the robustness of the proposed algorithm by applying it to two types of data acquired at actual construction sites. This approach is expected to contribute significantly to the digital transformation in the construction industry.
期刊介绍:
Developments in the Built Environment (DIBE) is a recently established peer-reviewed gold open access journal, ensuring that all accepted articles are permanently and freely accessible. Focused on civil engineering and the built environment, DIBE publishes original papers and short communications. Encompassing topics such as construction materials and building sustainability, the journal adopts a holistic approach with the aim of benefiting the community.