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BIM기반 설계데이터 평가 시스템 개선을 위한 ChatGPT활용 방법론A Methodology for Using ChatGPT to Improve BIM-based Design Data Evaluation System

Other Titles
A Methodology for Using ChatGPT to Improve BIM-based Design Data Evaluation System
Authors
유은상김구택안용한최중식
Issue Date
Jun-2024
Publisher
한국BIM학회
Keywords
건설정보모델링; 건축 AI; 설계 데이터 자동화 평가; 챗GPT BIM; Architectural AI; Design Data Automation Evaluation; ChatGPT
Citation
KIBIM Magazine, v.14, no.2, pp 25 - 34
Pages
10
Indexed
KCI
Journal Title
KIBIM Magazine
Volume
14
Number
2
Start Page
25
End Page
34
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/120448
ISSN
22881697
Abstract
This study proposes a new methodology to increase the flexibility and efficiency of the design data evaluation system by combining Building Information Modeling (BIM) technology in the architectural industry, OpenAI's interactive artificial intelligence, and ChatGPT. BIM technology plays an important role in digitally modeling and managing architectural information. Since architectural information is included, research and development are underway to review and evaluate BIM data according to conditions through program development. However, in the process of reviewing BIM design data, if the review criteria or evaluation criteria according to design change occur frequently, it is necessary to update the program anew. In order for designers or reviewers to apply the changed criteria, requesting a program developer will delay time. This problem was studied by using ChatGPT to modify and update the design data evaluation program code in real time. In this study, it is aimed to improve the changing standards and accuracy by enabling programming non-professionals to change the design regulations and calculation standards of the BIM evaluation program system using ChatGPT. In this study, in the BIM-based design certification automation evaluation program, a program in which the automation evaluation method is being studied based on the design certification evaluation manual was first used. In the design certification automation evaluation program, the programming non-majors checked the automation evaluation code by linking ChatGPT, and the changed calculation criteria were created and modified interactively. As a result of the evaluation, the change in the calculation standard was explained to ChatGPT and the applied result was confirmed.
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COLLEGE OF ENGINEERING SCIENCES > MAJOR IN ARCHITECTURAL ENGINEERING > 1. Journal Articles

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Ahn, Yong Han
ERICA 공학대학 (MAJOR IN ARCHITECTURAL ENGINEERING)
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