{"title":"Mixed Reality-based MEP construction progress monitoring: Evaluation of methods for mesh-to-mesh comparison","authors":"Boan Tao, Frédéric Bosché, Jiajun Li","doi":"10.1016/j.autcon.2024.105852","DOIUrl":null,"url":null,"abstract":"<div><div>Visually monitoring progress and geometric quality on site using Mixed Reality (MR) and overlaid Building Information Model (BIM model) is challenging, particularly in complex contexts like complex mechanical, electrical, and plumbing (MEP) systems. This paper proposes and evaluates four individual methods and three combined ones for automated object recognition and deviation evaluation, based on the matching and comparison of the 3D mesh captured on site by MR systems with the mesh geometry of the elements in the (as-designed) BIM model. The four individual methods include: (1) Bounding Box Occupation, (2) Point-to-Surface Distance, (3) Voxel Occupation, (4) Feature Matching. Three combined methods are Method <span><math><mrow><mn>1</mn><mo>∪</mo><mn>4</mn></mrow></math></span>, Method <span><math><mrow><mn>2</mn><mo>∪</mo><mn>4</mn></mrow></math></span> and Method <span><math><mrow><mn>3</mn><mo>∪</mo><mn>4</mn></mrow></math></span> (i.e. combining methods 1 and 4, 2 and 4, and 3 and 4, respectively). The methods are evaluated using both synthetic and real data of MEP construction works, with the Method <span><math><mrow><mn>1</mn><mo>∪</mo><mn>4</mn></mrow></math></span> yielding the best performance.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"168 ","pages":"Article 105852"},"PeriodicalIF":9.6000,"publicationDate":"2024-11-08","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/S0926580524005880","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
Visually monitoring progress and geometric quality on site using Mixed Reality (MR) and overlaid Building Information Model (BIM model) is challenging, particularly in complex contexts like complex mechanical, electrical, and plumbing (MEP) systems. This paper proposes and evaluates four individual methods and three combined ones for automated object recognition and deviation evaluation, based on the matching and comparison of the 3D mesh captured on site by MR systems with the mesh geometry of the elements in the (as-designed) BIM model. The four individual methods include: (1) Bounding Box Occupation, (2) Point-to-Surface Distance, (3) Voxel Occupation, (4) Feature Matching. Three combined methods are Method , Method and Method (i.e. combining methods 1 and 4, 2 and 4, and 3 and 4, respectively). The methods are evaluated using both synthetic and real data of MEP construction works, with the Method yielding the best performance.
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.