Skip to main content
SpringerLink
Log in

Employment of Semantic Web Technologies for Capturing Comprehensive Parametric Building Models

  • Conference paper
  • First Online:
Advances in Informatics and Computing in Civil and Construction Engineering

Abstract

Building Information Modelling is a well-known acronym in the construction industry. BIM process is more than modelling buildings, and it provides the opportunity to drive efficiency and effectiveness to the information management of build projects. Accordingly, Building Information Models (BIMs), typically known as semantic three-dimensional parametric models, are fast becoming the comprehensive information source in Architecture, Engineering and Construction (AEC), and Facility Management (FM). The use of BIM in existing buildings has been hampered by the challenges and limitations surrounding the available technologies. The most popular and commonly used approach for generating models is to manually generate 3D artefacts utilizing point measurements extracted from range-based technologies (typically 3D laser scanning). In the recent past, several studies have been carried out to make the retro t BIM development process as effective and efficient as possible by developing different methods for mapping 3D models using Point Cloud Data (PCD) as the main source of information. However, an appropriate fully generated parametric model is still some way away. In this paper, we review the-state-of-the-art to address the research gap and challenges involved in generating parametric models before outlining the proposal of our approach. In this research, we employ Semantic Web technologies to capture parametric models. Elements are first recognized in PCD, and corresponding geometric information extracted from PCD are then tagged with Universally Unique Identifiers (UUIDs). Tags are then linked with the generated Resource Description Framework (RDF) data for each element. The core and challenging part of this research is the standardization process where RDF as a serialization is translated to Industry Foundation Classes (IFC) as a data model. The generated IFC format is then utilized to capture corresponding models. The primary results are very promising and should be of interest to the modelling of all kinds of building components, particularly historical building information modelling (HBIM).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 349.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 449.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 449.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Volk, R., Stengel J., Schultmann, F.: Building information modeling (BIM) for existing buildings—literature review and future needs. Autom. Constr. 38, 109–127 (2014)

    Google Scholar 

  2. Zhang, S., Teizer, J., Lee, J.-K., Eastman, C. M., Venugopal, M.: Building information modeling (BIM) and safety: automatic safety checking of construction models and schedules. Autom. Constr. 29, 183–195 (2013)

    Article  Google Scholar 

  3. Gao, T., Akinci, B., Ergan, S., Garrett, J.: An approach to combine progressively captured point clouds for BIM update. Adv. Eng. Inform. 29(4), 1001–1012 (2015)

    Article  Google Scholar 

  4. Hayne, G., Kumar, B., Hare, B.: The development of a framework for a design for safety BIM tool. In: Computing in Civil and Building Engineering, pp. 49–56, Orlando (2014)

    Google Scholar 

  5. Dore, C., Murphy, M.: Historic building information modelling (HBIM). In: Handbook of Research on Emerging Digital Tools for Architectural Surveying, Modeling, and Representation vol. 1, pp. 239–280 (2015)

    Google Scholar 

  6. Barazzetti, L.: Parametric as-built model generation of complex shapes from point clouds. Adv. Eng. Inform. 30(3), 298–311 (2016)

    Article  Google Scholar 

  7. Gao, T., Ergan, S., Akinci, B., Garrett, J.: Evaluation of different features for matching point clouds to building information models. J. Comput. Civil Eng. 30(1), 1–13 (2014)

    Article  Google Scholar 

  8. Zhang, G., Vela, P., A., Karasev, P., Brilakis, I.: A sparsity-inducing optimization-based algorithm for planar patches extraction from noisy point-cloud data. Comput. Aided Civil Infrastruct. Eng. 30(2), 85–102 (2015)

    Article  Google Scholar 

  9. Quattrini, R., Malinverni, E., Clini, P., Nespeca, R., Orlietti, E.: From TLS to HBIM. High quality semantically-aware 3D modeling of complex architecture. In: The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 40, No. 5, pp. 367–374 (2015)

    Google Scholar 

  10. Wang, C., Cho, Y.K., Kim, C.: Automatic BIM component extraction from point clouds of existing buildings for sustainability applications. Autom. Constr. 56, 1–13 (2015)

    Article  Google Scholar 

  11. Colomina, I., Molina, P.: Unmanned aerial systems for photogrammetry and remote sensing: a review. ISPRS J. Photogram. Remote Sens. 92, 79–97 (2014)

    Article  Google Scholar 

  12. Herraez, J., Martinez, J.C., Coll, E., Martin, M.T., Rodriguez, J.: 3D modeling by means of videogrammetry and laser scanners for reverse engineering. Measurement 87, 216–227 (2016)

    Article  Google Scholar 

  13. Bosche, F., Forster, A., Valero, E.: 3D Surveying Technologies and Applications: Point Clouds and Beyond. Heriot-Watt University, Edinburgh (2015)

    Google Scholar 

  14. Son, H., Kim, C.: Automatic segmentation and 3D modeling of pipelines into constituent parts from laser-scan data of the built environment. Autom. Constr. 68, 203–211 (2016)

    Article  Google Scholar 

  15. Xiong, X., Adan, A., Akinci, B., Huber, D.: Automatic creation of semantically rich 3D building models from laser scanner data. Autom. Constr. 31, 325–337 (2013)

    Article  Google Scholar 

  16. Adan, A., Huber, D.: 3D reconstruction of interior wall surfaces under occlusion and clutter. In 3D Imaging, Modeling. In: 2011 International Conference on Processing, Visualization and Transmission (3DIMPVT), 275–281, IEEE (2011)

    Google Scholar 

  17. Barazzetti, L., Ban, F., Brumana, R., Roncoroni, F., Previtali, M.: BIM from laser scans not just for buildings: NURBS-based parametric modeling of a medieval bridge. In: ISPRS Conference, pp. 51–56 (2016)

    Article  Google Scholar 

  18. Oreni, D., Brumana, R., Della Torre, S., Ban, F., Previtali, M.: Survey turned into HBIM: the restoration and the work involved concerning the Basilica di Collemaggio after the earthquake (L’Aquila). ISPRS Ann. Photogram. Remote Sens. Spat. Inf. Sci. 2(5), 267–273 (2014)

    Article  Google Scholar 

  19. Murphy, M., McGovern, E., Pavia, S.: Historic building information modelling adding intelligence to laser and image based surveys of European classical architecture. ISPRS J. Photogram. Remote Sens. 76, 89–102 (2013)

    Article  Google Scholar 

  20. Barazzetti, L., Ban, F., Brumana, R., Gusmeroli, G., Oreni, D., Previtali, M., Roncoroni, F., Schiantarelli, G.: BIM from laser clouds and nite element analysis: combining structural analysis and geometric complexity. Int. Arch. Photogram. Remote Sens. Spat. Inf. Sci 40(5), 345–350 (2015)

    Article  Google Scholar 

  21. McGibbney, L.J., Kumar, B.: A framework for regulatory ontology construction within AEC domain. In: Ontology in the AEC Industry, pp. 193–215 (2015)

    Chapter  Google Scholar 

  22. Quattrini, R., Pierdicca, R., Morbidoni, C.: Knowledge-based data enrichment for HBIM: exploring high-quality models using the semantic-web. J. Cult. Heritage 28, 129–139 (2017)

    Article  Google Scholar 

  23. Yu, L.: A Developers Guide to the Semantic Web. Springer Science & Business Media (2011)

    Google Scholar 

  24. Domingue, J., Fensel, D., Hendler, J.A. eds.: Handbook of semantic web technologies. Springer Science & Business Media, (2011)

    Google Scholar 

  25. Powers, S.: Practical RDF: Solving Problems With the Resource Description Framework. O’Reilly Media, Inc. (2003)

    Google Scholar 

  26. Logothetis, S., Delinasiou, A., Stylianidis, E.: Building information modelling for cultural heritage: a review. ISPRS Ann. Photogram. Remote Sens. Spat. Inf. Sci. 2(5), 177–183 (2015)

    Article  Google Scholar 

  27. Oreni, D., Brumana, R., Georgopoulos, A., Cuca, B.: HBIM for conservation and management of built heritage: towards a library of vaults and wooden beam floors. ISPRS Ann. Photogram. Remote Sens. Spat. Inf. Sci. 5, 215–221 (2013)

    Article  Google Scholar 

  28. Borrmann, A., Rank, E.: Specification and implementation of directional operators in a 3D spatial query language for building information models. Adv. Eng. Inform. 23(1), 32–34 (2009)

    Article  Google Scholar 

  29. Pauwels, P., Van Deursen, D., Verstraeten, R., De Roo, J., De Meyer, R., Van de Walle, R., Van Campenhout, J.: A semantic rule checking environment for building performance checking. Autom. Constr. 20(5), 506–518 (2011)

    Article  Google Scholar 

  30. Sadeghineko, F., Kumar, B., Chan, W.: A semantic web-based approach for generating parametric models using RDF. In: Workshop of the European Group for Intelligent Computing in Engineering, pp. 361–377, Springer, Cham (2018)

    Chapter  Google Scholar 

  31. Beetz, J., Borrmann, A.: Benefits and limitations of linked data approaches for road modeling and data exchange. In: Workshop of the European Group for Intelligent Computing in Engineering, pp. 245–261, Springer, Cham (2018)

    Chapter  Google Scholar 

  32. Logothetis, S., Karachaliou, E., Stylianidis, E.: From OSS CAD to BIM for cultural heritage digital representation. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 3D Virtual Reconstruction and Visualization of Complex Architectures vol. XLII-2(W3), pp. 439–445 (2017)

    Article  Google Scholar 

  33. Lopez, F., Lerones, P., M., Llamas, J., Gomez-Garcia-Bermejo, J., Zalama, E.: A review of heritage building information modeling (H-BIM). Multimodal Technol. Interact. 2(2), 1–29 (2018)

    Article  Google Scholar 

Download references

Acknowledgements

Authors would like to express their gratitude to Dr. Vajira Premadasa of Historic Environment Scotland (HES) for providing assistance and support in the research presented in this paper.

Author information

Authors and Affiliations

  1. Construction and Surveying Department, Glasgow Caledonian University, Glasgow, G4 0BA, UK

    Farhad Sadeghineko

  2. Architecture and Built Environment, Northumbria University, Newcastle, NE1 8ST, UK

    Bimal Kumar

  3. Computer, Communications and Interactive Systems, Glasgow Caledonian University, Glasgow, G4 0BA, UK

    Warren Chan

Authors
  1. Farhad Sadeghineko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bimal Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Warren Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Farhad Sadeghineko .

Editor information

Editors and Affiliations

  1. CAEE, Illinois Institute of Technology, Chicago, IL, USA

    Ivan Mutis

  2. Institute of Civil Engineering, TU Berlin, Berlin, Germany

    Timo Hartmann

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sadeghineko, F., Kumar, B., Chan, W. (2019). Employment of Semantic Web Technologies for Capturing Comprehensive Parametric Building Models. In: Mutis, I., Hartmann, T. (eds) Advances in Informatics and Computing in Civil and Construction Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-00220-6_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-00220-6_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00219-0

  • Online ISBN: 978-3-030-00220-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation