Acknowledgement
본 연구는 한국과학재단이 주관하는 대학 중점연구소지원사업(No. NRF-2018R1A6A1A07025819)과 신진연구지원사업(No. NRF-2020R1C1C1005406)의 지원을 받아 수행되었습니다.
It is considered that the construction industry is one of the pivotal players in the national economy in terms of Gross Domestic Production (GDP) and employment. Behind the positive role of this industrial sector to the national economy, the construction industry generates approximately 50 % of the total waste generation from all the industrial sectors. There are several measures to mitigate the adverse impacts of the construction waste such as reduce, reuse and recycle. Recycling would be one of the effective strategies for waste minimisation, which would be able to reduce the demand upon new resources as well as enhance reusing the construction materials on sites. The automated construction waste classification system would make it possible not only to reduce the amount of labour input but also mitigate the possibility of errors during the manual classification process. In this study, we proposed an automated waste segmentation and classification system for recycling the construction and demolition waste in the real construction site context. Since the practical application to the real-world construction sites was one of the significant factors to develop the system, a YOLACT (You Only Look At CoefficienTs) algorithm was chosen to conduct the study. In this study, it is expected that the proposed system would make it possible to enhance the productivity as well as the cost efficiency by reducing the manpower for the construction and demolition waste management at the construction site.
본 연구는 한국과학재단이 주관하는 대학 중점연구소지원사업(No. NRF-2018R1A6A1A07025819)과 신진연구지원사업(No. NRF-2020R1C1C1005406)의 지원을 받아 수행되었습니다.