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오경석(Kyungseok Oh),김원호(Wonho Kim),공정환(Junghwan Gong),이승환(Seunghwan Lee) 대한전기학회 2021 대한전기학회 학술대회 논문집 Vol.2021 No.10
기존연구에서는 인간 추적을 위해 딥러닝 API인 Detectron2기반의 Faster R-CNN 모델을 활용한 방법이 제안되었다. 하지만, Detectron2기반 방법의 정확도는 우수하지만 실시간 적용에 어려움이 있다. 따라서, 본 논문에서는 인간 탐지를 위해 YOLOv3 모델을 이용하여 인간 추적 속도를 개선하고자 하였다. 실험을 통해 기존연구에 비해 제안한 방법의 추적속도가 크게 향상됨을 보였다.
BIM과 LCA를 이용한 건축물 리모델링에 따른 온실가스 배출량 분석 - 건축물 외장재를 중심으로 -
김소현(Sohyun Kim),남궁환(Hwan Namgung),오경석(Kyungseok Oh),정광복(Kwangbok Jeong),이재욱(Jaewook Lee) 한국생태환경건축학회 2024 한국생태환경건축학회 논문집 Vol.24 No.1
Purpose: As the construction industry accounts for a significant portion of global carbon dioxide emissions, the importance of reducing carbon emissions through the remodeling of existing buildings is being emphasized. This study proposes a method to evaluate the greenhouse gas emissions of each building material in the remodeling process of existing buildings by integrating BIM and LCA, and visualizing this in a BIM model. Method: Using BIM models, the quantity and cost of each material are calculated, and the greenhouse gas emissions are evaluated through LCA. Then, these are visualized in the BIM model using a Dynamo-based parametric algorithm. This study analyzed the total greenhouse gas emissions of five types of exterior materials, including the existing exterior material, through a case study. Result: The study results showed that stucco has the lowest greenhouse gas emissions, while exposed concrete has the highest. This suggests that remodeling with stucco could be an effective strategy to minimize greenhouse gas emissions when considering the entire life cycle of a building. Additionally, the process of visualizing the environmental impact of each exterior material in the BIM model, where the colors of BIM objects change automatically based on their impact, provides a way for even non-experts to easily understand LCA data. This approach can significantly contribute to the selection of sustainable building materials and the improvement of environmental impacts of buildings.