Digitising Building Materials for Reuse with Reality Capture and Scan-to-BIM Technologies

Author:

Gordon Matthew,von Zimmerman Luise,Haradhun Oushesh,Campanella Dominik,Bräutigam Milena,De Wolf Catherine

Abstract

AbstractEffective building component reuse requires specific information about recoverable components. However, 85% of the European building stock predates the building information modelling (BIM) technology that stores and links such information. Digitisation technologies can be used to recover this information. Scanning and scan-to-BIM technologies such as LiDAR and photogrammetry enable us to capture and analyse large amounts of raw geometric data as point clouds to create digital records or BIM models of existing buildings. These digital representations can be used by building owners, inspectors, and deconstruction groups for deconstruction, new design, procurement, and new construction. They help implement closed circular resource strategies linking recovered materials to new projects. In this article, we look at a specific case study of these applications through the circularity consultant Concular. Digitisation technologies are compared based on their range and accuracy in conditions with noisy and cluttered data, as well as their cost and accessibility. Additional sensor technologies may integrate further compositional or structural details to ultimately produce insights beyond surface geometry that can be communicated through integrated digital platforms for data access and exchange. Further technological development will lower the time and labour costs during data collection, processing, and analysis.

Publisher

Springer International Publishing

Reference32 articles.

1. Adamopoulos E, Rinaudo F (2021) Close-range sensing and data fusion for built heritage inspection and monitoring—a review. Remote Sens 13(19):3936. https://doi.org/10.3390/rs13193936

2. Bello SA, Yu S, Wang C, Adam JM, Li J (2020) Review: deep learning on 3D point clouds. Remote Sens 12(11):1729. https://doi.org/10.3390/rs12111729

3. Charef R, Emmitt S, Alaka H, Fouchal F (2019) Building information modelling adoption in the european union: an overview. J Build Eng 25:100777. https://doi.org/10.1016/j.jobe.2019.100777

4. Concular (2021) Ausgewählte Projekte – Concular - Zirkuläres Bauen : Concular – Zirkuläres Bauen. https://concular.de/projekte/. Accessed 6 Feb 2023

5. Deloitte (2019) Complexity: overcoming obstacles and seizing opportunities. The Deloitte global chief procurement officer survey 2019. In: Deloitte Insights. https://www2.deloitte.com/si/en/pages/strategy-operations/articles/global-cpo-survey.html. Accessed 7 Feb 2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3