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Applied Sciences
Special Issues
Building Information Modeling (BIM): Advance and Future Trends
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Building Information Modeling (BIM): Advance and Future Trends

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 20 October 2024 | Viewed by 849

Special Issue Editor

Dr. Valentin Gomez-Jauregui

E-Mail Website
Guest Editor
Research Group EgiCAD, School of Civil Engineering, Geographical Engineering and Graphic Expression Techniques, Universidad de Cantabria, Santander, Spain
Interests: BIM; tensegrity; augmented reality; virtual reality

Special Issue Information

Dear Colleagues,

This Special Issue aims to identify the key pathways that the BIM methodology will need to follow in the future to address the challenges, needs, and uncertainties in the AEC sector.

In recent years, the advancement of the BIM methodology has been evolving through standards, revisions, updates, and improvements, with the goal of finding the essential elements that will make it the perfect technology for the construction industry. With the idea of completing the concept of a virtual model and digital twin, BIM is conceived as a methodology that creates a unique model for each project, allowing for digital design simulations, with a focus on information, transparency, and collaboration.

However, what are the current seeds that will sprout to meet the future needs of the industry and construction? Connectivity and programming are the keys to the future after BIM, but we must not forget the potential of artificial intelligence, applied Big Data, and machine learning.

The potential topics of this Special Issue include, but are not limited to:

  • New perspectives and trends in Building Information Modeling (BIM).
  • Simulations with virtual models and digital twins through BIM.
  • Virtual reality, augmented reality, mixed reality, and extended reality with BIM.
  • Connectivity of the real world with BIM projects.
  • Programming on BIM.
  • Computational and data science applied to BIM.
  • Big data applications, algorithms, and systems on BIM.
  • Evolution of BIM
  • Innovative solutions on BIM for the construction industry.
  • Artificial intelligence, machine learning, and deep learning applied to BIM.
  • Development of software for new solutions on BIM.
  • BIM and new materials.

I hope you will contribute your high-quality research and I look forward to reading your valuable results.

Dr. Valentin Gomez-Jauregui
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • BIM
  • programming
  • connectivity
  • virtual reality
  • augmented reality
  • mixed reality
  • extended reality
  • big data
  • AI
  • machine learning
  • deep learning

Published Papers (1 paper)

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Research

43 pages, 21801 KiB  
Article
Using Dynamo for Automatic Reconstruction of BIM Elements from Point Clouds
by Gustavo Rocha and Luís Mateus
Appl. Sci. 2024, 14(10), 4078; https://doi.org/10.3390/app14104078 - 10 May 2024
Viewed by 556
Abstract
The integration of 3D laser scanning and digital photogrammetry in the architecture, engineering, and construction (AEC) industry has facilitated high-quality architectural surveys. However, the processes remains constrained by significant costs, extensive manual labor, and accuracy issues associated with manual data processing. This article [...] Read more.
The integration of 3D laser scanning and digital photogrammetry in the architecture, engineering, and construction (AEC) industry has facilitated high-quality architectural surveys. However, the processes remains constrained by significant costs, extensive manual labor, and accuracy issues associated with manual data processing. This article addresses these operational challenges by introducing automated Building Information Modeling (BIM) techniques that minimize manual input through the use of Dynamo for Autodesk Revit. We developed algorithms that efficiently convert point cloud data into accurate BIM models, enhancing productivity and reducing the potential for errors. The application of these algorithms is analyzed in a case study of the Old Lifeguard Station of Fuseta, showcasing notable reductions in modeling time and improvements in accuracy. The findings suggest that automated scan-to-BIM methods could provide a viable solution for enhancing BIM workflows across the industry, with the potential for wider adoption given their impact on efficiency and model quality. Full article
(This article belongs to the Special Issue Building Information Modeling (BIM): Advance and Future Trends)
►▼ Show Figures

Figure 1

Figure 1
<p>Summary of the five phases of this research.</p> Full article ">Figure 2
<p>Survey of the Old Lifeguard Station of Fuseta building, Portugal.</p> Full article ">Figure 3
<p>Summary of the three basic stages of operation for BIM modeling automation algorithms.</p> Full article ">Figure 4
<p>Example of the point selection procedure in the point cloud for using the algorithms.</p> Full article ">Figure 5
<p>Diagram of the solution developed for the topography automation modeling algorithm.</p> Full article ">Figure 6
<p>Dynamo’s automatic topography modeling algorithm for Revit using point clouds.</p> Full article ">Figure 7
<p>(<b>a</b>) Segmented point cloud classified with ground points, (<b>b</b>) BIM topo surface created in Revit using the algorithm developed with Dynamo.</p> Full article ">Figure 8
<p>(<b>a</b>) Image showing the type and state of conservation of the structural columns from the base of the building. (<b>b</b>) Illustrative image of the existing deviations in the columns.</p> Full article ">Figure 9
<p>Diagram of the solution developed for the structural column automation modeling algorithm.</p> Full article ">Figure 10
<p>(<b>a</b>) Algorithm developed with Dynamo for automatic detection and modeling of structural columns. (<b>b</b>) Point cloud used. (<b>c</b>) The BIM elements created in Revit using the Dynamo algorithm.</p> Full article ">Figure 11
<p>(<b>a</b>) Photo of the column built into the wall. (<b>b</b>) The floor plan showing the embedded column and the distance inside the wall is controlled by the user with defined parameters when using the algorithm.</p> Full article ">Figure 12
<p>(<b>a</b>) Image of the structural beams of the building and their conservation conditions. (<b>b</b>) Illustrative image of the existing deviations in the structural beams.</p> Full article ">Figure 13
<p>Diagram of the solution developed for the structural beam automation modeling algorithm.</p> Full article ">Figure 14
<p>(<b>a</b>) The algorithm developed with Dynamo for automatic detection and modeling of structural beams. (<b>b</b>) Point cloud used. (<b>c</b>) BIM elements created in Revit using the Dynamo algorithm.</p> Full article ">Figure 15
<p>Diagram of the solution developed for the wall automation modeling algorithm.</p> Full article ">Figure 16
<p>(<b>a</b>) The algorithm developed with Dynamo for automatic detection and modeling of walls. (<b>b</b>) Point cloud used. (<b>c</b>) BIM elements created in Revit using the Dynamo algorithm.</p> Full article ">Figure 17
<p>Diagram of the solution developed for the floor and roof automation modeling algorithm.</p> Full article ">Figure 18
<p>(<b>a</b>) The algorithm developed with Dynamo for automatic detection and modeling of floor and roof. (<b>b</b>) Point cloud used. (<b>c</b>) BIM elements created in Revit using the Dynamo algorithm.</p> Full article ">Figure 19
<p>BIM model of the Old Lifeguard Station of Fuseta building created with automatic, semi-automatic, and manual approaches.</p> Full article ">Figure 20
<p>Floor plan of the main level of the Old Lifeguard Station of Fuseta building.</p> Full article ">Figure 21
<p>Level of accuracy of elements modeled by the algorithm with automatic and semi-automatic approaches compared to the point cloud obtained from the terrestrial 3D laser scanning of the existing building.</p> Full article ">Figure 22
<p>Level of accuracy of elements modeled with the manual approach compared to the point cloud obtained from the terrestrial 3D laser scanning of the existing building.</p> Full article ">Figure 23
<p>Charts comparing the accuracy between models created by automatic and manual modeling approaches. (<b>a</b>) Percentage of points for accuracy of up to 12 mm. (<b>b</b>) Percentage of points for accuracy of up to 25 mm. (<b>c</b>) The average accuracy of all elements.</p> Full article ">Figure A1
<p>Topography modeling algorithm.</p> Full article ">Figure A2
<p>Structural column modeling algorithm—part 1.</p> Full article ">Figure A3
<p>Structural column modeling algorithm—part 2.</p> Full article ">Figure A4
<p>Structural column modeling algorithm—part 3.</p> Full article ">Figure A5
<p>Structural beam modeling algorithm—part 1.</p> Full article ">Figure A6
<p>Structural beam modeling algorithm—part 2.</p> Full article ">Figure A7
<p>Structural beam modeling algorithm—part 3.</p> Full article ">Figure A8
<p>Wall modeling algorithm—part 1.</p> Full article ">Figure A9
<p>Wall modeling algorithm—part 2.</p> Full article ">Figure A10
<p>Floor modeling algorithm—part 1.</p> Full article ">Figure A11
<p>Floor modeling algorithm—part 2.</p> Full article ">Figure A12
<p>Floor modeling algorithm—part 3.</p> Full article ">
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