Embodied Carbon Upfront Data Calculation Using an Integrated BIM Power BI Approach
1
Issued Date
2025-01-01
Resource Type
ISSN
23662557
eISSN
23662565
Scopus ID
2-s2.0-105020020389
Journal Title
Lecture Notes in Civil Engineering
Volume
726 LNCE
Start Page
31
End Page
37
Rights Holder(s)
SCOPUS
Bibliographic Citation
Lecture Notes in Civil Engineering Vol.726 LNCE (2025) , 31-37
Suggested Citation
Phonna N., Sripattana S., Punurai W., Pratharnsap T. Embodied Carbon Upfront Data Calculation Using an Integrated BIM Power BI Approach. Lecture Notes in Civil Engineering Vol.726 LNCE (2025) , 31-37. 37. doi:10.1007/978-981-95-0090-1_5 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/112901
Title
Embodied Carbon Upfront Data Calculation Using an Integrated BIM Power BI Approach
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Author's Affiliation
Corresponding Author(s)
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Abstract
Digital technologies have transformed the Architecture, Engineering and Construction (AEC) sector. They are changing how built assets are designed, constructed and operated. The technologies used include building information modelling (BIM), prefabrication, wireless sensors, 3D printing and automated robotic equipment. With these technologies, more buildings will be built quicker while still supporting environmental regulations. Given that buildings contribute about 40% of greenhouse gas emissions worldwide, the industry can now implement a sustainable whole life carbon approach, and use the tools available to assist them in accelerating the transition towards net zero carbon buildings by 2050. In this research, an integrated system tool based on Dynamo Revit plug-in and PowerBI is developed for the extraction and visualization of the EC upfront for new building construction. The system tool is based on Dynamo programming for information extraction and creating the visualization of the EC impacts of the materials choices in the form of dashboards on PowerBI. Additionally, Dynamo scripts were used for adding project-material data directly from the Thailand Greenhouse Gas Management Organization (TGO) or EC3 database and to automate the execution of Dynamo for each of the analyses performed in this research. The effectiveness and usability of the approach are validated using a case study and the KITCARBON platform.