Algorithm of Smart Building Supervision for Detecting and Counting Column Ties Using Deep Learning

Abstract

The Building Supervision of South Korea has been developed under the government′s desire to prevent poor construction and improve the quality of buildings to promote a safer life for the people. Although the building environment of today has been achieved through several improvements, the introduction of such technology is insufficient. Especially since building supervision is primarily carried out almost by manpower, in an era where numerous convergence technologies from the 4th industry are being utilized. Therefore, this study aimed to solve this inefficiency in the building supervision system by using the object detection technology of deep learning in the BIM environment. As a basic study to develop a smart supervision checking system that checks whether the information on the construction site matches the design information, the column ties were selected as a supervision item, and research was conducted. For this, we constructed the tie detection network and suggested an algorithm for information checking between the construction site and BIM environment. Through this, it was possible to confirm the possibility of practical supervision work and improve the efficiency of the work, and furthermore, to see the possibility of using convergence technology.