Skip to main content
SpringerLink
Log in

The Practical Implications of Using Fuzzy Logic for Mapping Data for Life Cycle Analysis

  • Conference paper
  • First Online:
Cooperative Design, Visualization, and Engineering (CDVE 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13492))

  • 520 Accesses

Abstract

For the last decade, the focus on sustainability has increased significantly. In the Architectural, Engineering, and Construction industry (AEC), the focus of sustainability is on making a Life Cycle Analysis (LCA) on the different building components. Research indicates that the collaboration between disciplines is limited because of human linguistic failure in BIM models. This research aims to bring forth the principles of mapping data with fuzzy logic algorithms and show the application in a practical collaborative context. With the application of Design Science Research methodology, this research will create an artifact in Dynamo for Revit, with the implementation of fuzzy logic algorithms for mapping LCA data from LCAbyg, is an LCA-program used in the danish AEC industry, and the linguistic data from a BIM model. The research shows that the implementation of a fuzzy logic system is an effective tool for mapping data. The result of the prototype concludes that fuzzy logic algorithms with ease can be used in a collaborative context. The study implies that the AEC industry’s linguistic difference and purity are a limitation on using fuzzy logic algorithms. The research also indicates that the fuzzy logic algorithm used in parallel constellation may cause bad results, and the relegation or exclusion of different algorithms should be investigated. The research also shows that the linguistic deficiencies in LCAbyg concerning the applied linguistic of the industry have a significant implication on fuzzy logic.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Pradeep, A.S.E., Amor, R., Yiu, T.W.: Blockchain improving trust in BIM data exchange: a case study on BIMCHAIN. In: Construction Research Congress 2020, 1384 p (2020)

    Google Scholar 

  2. Zadeh, L.: Fuzzy Set* (1965)

    Google Scholar 

  3. Lofti, Z.: Soft computing and fuzzy logic. IEEE Softw. 12, 48–56 (1994)

    Google Scholar 

  4. Sharma, S., Goyal, P.K.: Applying “fuzzy techniques” in construction project management (2019)

    Google Scholar 

  5. Klashanov, F.: Fuzzy logic in construction management. MATEC Web Conf. 170, 1–6 (2018). https://doi.org/10.1051/matecconf/201817001111

  6. Chan, A.P.C., Chan, D.W.M., Yeung, J.F.Y.: Overview of the application of “fuzzy techniques” in construction management research. J. Constr. Eng. Manag. 135, 1241–1252 (2009). https://doi.org/10.1061/(ASCE)CO.1943-7862.0000099

    Article  Google Scholar 

  7. Tiruneh, G.G., Fayek, A.R., Sumati, V.: Neuro-fuzzy systems in construction engineering and management research. Autom. Constr. 119, 103348 (2020). https://doi.org/10.1016/j.autcon.2020.103348

    Article  Google Scholar 

  8. Cavalliere, C., Brescia, L., Maiorano, G., Dalla Mora, T., Dell’Osso, G.R., Naboni, E.: Towards an accessible life cycle assessment: a literature based review of current BIM and parametric based tools capabilities. In: Polytechnic University of Bari, Bari, Italy The Royal Danish Academy of Fine Arts Schools of Architecture, Design and Conservation, pp. 159–166 (2019). https://doi.org/10.26868/25222708.2019.210634

  9. Hollberg, A., Ruth, J.: LCA in architectural design—a parametric approach. Int. J. Life Cycle Assess. 21(7), 943–960 (2016). https://doi.org/10.1007/s11367-016-1065-1

    Article  Google Scholar 

  10. Rasmussen, F.N., Zimmermann, R.K., Kanafani, K., Andersen, C., Birgisdóttir, H.: The choice of reference study period in building LCA - case-based analysis and arguments. IOP Conf. Ser. Earth Environ. Sci. 588 (2020). https://doi.org/10.1088/1755-1315/588/3/032029

  11. Hollberg, A., Genova, G., Habert, G.: Evaluation of BIM-based LCA results for building design. Autom. Constr. 109, 102972 (2020). https://doi.org/10.1016/j.autcon.2019.102972

    Article  Google Scholar 

  12. Naneva, A., Bonanomi, M., Hollberg, A., Habert, G., Hall, D.: Integrated BIM-based LCA for the entire building process using an existing structure for cost estimation in the swiss context. Sustainability 12, 3748 (2020). https://doi.org/10.3390/su12093748

    Article  Google Scholar 

  13. Autodesk: Revit BIM software. https://www.autodesk.dk/products/revit/overview?term=1-YEAR

  14. Autodesk: Dynamo for Revit. https://knowledge.autodesk.com/support/revit-products/learn-explore/caas/CloudHelp/cloudhelp/2018/ENU/Revit-Customize/files/GUID-768D1E37-10CC-405D-A9D4-E2D5CF4224E5-htm.html

  15. Statens Byggeforskningsinstitut. Aalborg Universitet København. LCAbyg. https://lcabyg.dk/. Accessed 23 Mar 2021

  16. International: JSON Format. https://www.json.org/json-en.html. Accessed 23 Mar 2021

  17. Venable, J.R., Pries-Heje, J., Baskerville, R.: Choosing a design science research methodology. In: Proceedings of 28th Australasian Conference on Information Systems, ACIS 2017 (2017)

    Google Scholar 

  18. Esearch, S.Y.R., Hevner, B.A.R., March, S.T., Park, J., Ram, S.: Design science in information systems research. MIS Q. 28, 75–105 (2004)

    Article  Google Scholar 

  19. Peffers, K., Tuunanen, T., Rothenberger, M.A., Chatterjee, S.: A design science research methodology for information systems research. J. Manag. Inf. Syst. 24, 45–77 (2007). https://doi.org/10.2753/MIS0742-1222240302

    Article  Google Scholar 

  20. Peter, N.: Ecological BIM-based Model Checking Gade (2020)

    Google Scholar 

  21. Achi+lab: Bumblebee. https://archi-lab.net/bumblebee-dynamo-and-excel-interop/

  22. Jørgensen, E.F.: Orchid. https://dynamonodes.com/category/orchid/

  23. Dieckmann, A.: Clockwork for Dynamo. https://github.com/andydandy74/ClockworkForDynamo. Accessed 24 Mar 2021

  24. Kyle, M., Eric, R.: Fuzzydyno. https://dynamobim.org/fuzzy-string-matching/. Accessed 24 Mar 2021

  25. Kalra, S., Sriram, A., Rahnamayan, S., Tizhoosh, H.R.: Learning opposites using neural networks. In: 2016 23rd International Conference on Pattern Recognition, pp. 1213–1218 (2016). https://doi.org/10.1109/ICPR.2016.7899802

  26. Yogesh, G., Ashush, S.: Fuzzy logic-based approach to develop hybrid similarity measure for efficient informartion retrival. J. Inf. Sci. 12 (2014). https://doi.org/10.1177/0165551514548989

  27. Tizhoosh, H.R.: Fast fuzzy edge detection. In: 2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622), pp. 239–242. IEEE (2002). https://doi.org/10.1109/NAFIPS.2002.1018062

  28. Kang, H., Vachtsevanos, G.: Fuzzy hypercubes: linguistic learning/reasoning systems for intelligent control and identification. J. Intell. Robot. Syst. 7, 215–232 (1993). https://doi.org/10.1007/BF01257820

    Article  Google Scholar 

  29. Fletcher, S., Isla, M.Z.: Comparing sets of patterns with the Jaccard index. Australas. J. Inf. Syst. 22, 1–17 (2018). https://doi.org/10.3127/ajis.v22i0.1538

    Article  Google Scholar 

  30. Bentley, J., McIlroy, D.: Data compression using long common strings. In: Proceedings DCC 1999 Data Compression Conference (Cat. No. PR00096), pp. 287–295. IEEE (1999). https://doi.org/10.1109/DCC.1999.755678

Download references

Author information

Authors and Affiliations

  1. University College Northern Denmark, Aalborg, Denmark

    Peter Nørkjær Gade

  2. COWI, Århus, Denmark

    Thyge Otte Thomsen

Authors
  1. Peter Nørkjær Gade
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thyge Otte Thomsen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peter Nørkjær Gade .

Editor information

Editors and Affiliations

  1. University of Balearic Islands, Palma de Mallorca, Spain

    Yuhua Luo

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Gade, P.N., Thomsen, T.O. (2022). The Practical Implications of Using Fuzzy Logic for Mapping Data for Life Cycle Analysis. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2022. Lecture Notes in Computer Science, vol 13492. Springer, Cham. https://doi.org/10.1007/978-3-031-16538-2_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-16538-2_25

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16537-5

  • Online ISBN: 978-3-031-16538-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation