Development of Image-Based Artificial Intelligence Model to Automate Material Management at Construction Site

공사현장 자재관리 자동화를 위한 영상기반 인공지능 모델개발

Conventionally, in material management at a construction site, the type, size, and quantity of materials are identified by the eyes of the worker. Labor-intensive material management by manpower is slow, requires a lot of manpower, is prone to errors, and has limitations in that computerization of information on the identified types and quantities is additionally required. Therefore, a method that can quickly and accurately determine the type, size, and quantity of materials with a minimum number of workers is required to reduce labor costs at the construction site and improve work efficiency. In this study, we developed an automated convolution neural network(CNN) and computer vision technology-based rebar size and quantity estimation system that can quickly and accurately determine the type, size, and quantity of materials through images.