The Study of Feasibility to Project Monitoring with 3D Point Cloud Models on Precast House Models by C2C Algorithm and Python

Abstract

The construction industry is one of the industries that has to adapt to the ever-evolving technology development. Currently, the purpose of using technology in construction projects is to hasten the performance of the original system. and effective. In order to assess the viability of monitoring the advancement of a precast home project. This study collected data with unmanned aerial vehicles. Photographs taken with automatic flying system from the construction project at precast concrete walls on the day that the 1st floor section was completed and the 2nd floor section was completed. This study assesses the feasibility of assessing job progress. It is analyzed by the number of point clouds from Cloud compare software and Python and evaluated with the overlap of the model by the C2C algorithm. to find the differences of the 3D models from the two methods. The study found that the number of point clouds of the two methods differed less than 1% and differs from the schedule by 5 to 6 percent. The results from the comparison by evaluating model overlap with the C2C algorithm have the potential to develop concepts that can be used as one of the construction progress monitoring.