Construction site management involves overseeing tasks from the construction phase to the maintenance stage, and digitalization of construction sites is necessary for digital construction site management. In this study, we aim to conduct research on object recognition at construction sites using drones. Images of construction sites captured by drones are reconstructed into BIM (Building Information Modeling) models, and objects are recognized after partially rendering the models using artificial intelligence. For the photorealistic rendering of the BIM models, both traditional filtering techniques and the generative adversarial network (GAN) model were used, while the YOLO (You Only Look Once) model was employed for object recognition. This study is expected to provide insights into the research direction of digital construction site management and help assess the potential and future value of introducing artificial intelligence in the construction industry.
본 연구는 한국과학재단이 주관하는 대학 중점연구소지원사업(No. NRF-2018R1A6A1A07025819)과 국토교통부의 디지털 기반 건축시공 및 안전감리 기술개발사업(1615012983)의 지원을 받아 수행되었습니다.
References
Melenbrink. On-site autonomous construction robots: Towards unsupervised building. Elsevier. 2020. p. 119.
Seokjae Heo. Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry. MDPI. 2021. p. 11.