인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
This study introduces an optimized mobile-based Scan-to-BIM workflow designed to address the increasing demand for energy-efficient retrofitting of aging buildings. Traditional Scan-to-BIM methods often face challenges related to high costs and lengthy processing times, which restrict their practical application. In contrast, mobile LiDAR technology presents a more accessible and time-efficient solution. Field experiments were conducted at two renovation sites—a public health center and a community welfare facility—utilizing three iOS-based 3D scanning applications: 3D Scanner App™, RTAB-Map, and Polycam. These applications were evaluated based on point cloud quality, noise levels, registration performance, and 2D drawing accuracy. Among the applications, RTAB-Map yielded the most stable and geometrically accurate point clouds with minimal noise artifacts. In terms of processing speed, uBuilder excelled due to its simplified alignment algorithm. Drawing accuracy was measured using Mean Bias Error (MBE) and the Coefficient of Variation of the Root Mean Square Error (CVRMSE), both of which satisfied the monthly performance criteria outlined in ASHRAE Guideline 14. After a comprehensive assessment of accuracy and efficiency, the combination of RTAB-Map and uBuilder emerged as the optimal configuration. These findings offer valuable insights into the implementation of mobile Scan-to-BIM for digital documentation, thereby promoting sustainable renovation practices within the building sector.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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