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인공지능 기반 레빗-다이나모를 활용한 건축물의 화재안전관리

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Description

건축물의 안전관리를 위한 인공지능 기반의 사례 연구입니다. 다양한 재난 종류 중 특히 화재재난에 대응하는 건축물의 성능평가를 목표로 합니다. 본 사례는 Deep Learning 기술을 활용하여 건축물의 3D scan data로부터 BIM 모델을 자동으로 생성하고, 생성된 BIM 모델의 화재 관련 객체들을 분석하여 해당 건축물의 화재안전 성능을 평가하는 방법을 다루고 있습니다. 이를 통해, 리얼리티 캡쳐 기반 건축물 유지관리 및 성능평가에 대한 새로운 접근법을 확인할 수 있습니다.

Key Learnings

  • 이미 구축된 기존 건축물의 유지관리 및 성능평가를 위한 방법론을 확인 할 수 있습니다.
  • 3D Scanning및 인공지능을 활용한 디지털 트윈(Digital twin)의 구현 가능성을 알 수 있습니다.
  • 건축물의 자동 성능분석 기법에 대해서 알 수 있습니다.
  • -

Speakers

  • 재욱 이
    Jaewook Lee, Ph.D., is a professor of the Department of Architectural Engineering at Sejong University in Seoul, Korea. Dr. Lee has a Ph.D. in Design Computation from the University of California at Berkeley. His research interests lie in exploring the application of information technologies to architecture, which includes Artificial Intelligence for architectural design and construction, Building Information Modeling (BIM), disaster response of buildings, ICT-based building management, and smart city. Dr. Lee has served as the chief editor and vice-president of KIBIM (Korean Institute of Building Information Modelling).
  • 재홍 김
  • 동섭 서
  • Avatar for 준우 박준우 박
Current Time 0:00
Duration 33:50
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Stream Type LIVE
Remaining Time 33:50
 
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건축
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BIM(빌딩 정보 모델링)
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