Optimisation of 3D point cloud model for asset navigation

Abstract

An indoor asset is extremely important in building management and maintaining or increasing a building’s value. However, this indoor asset is hardly being tracked due to cumbersome methodology and techniques in the past. Hence, this study looked at the possibility of using a Terrestrial Laser Scanner (TLS) to acquire the internal dimension of the building in addition to the indoor asset. Furthermore, this study aimed to investigate an optimised approach to acquiring point cloud data for asset navigation applications. The objectives of this study were to identify the optimal configuration required, investigate the effect of multi-resolution, and access the navigation application with points cloud data. After a thorough investigation of the subject - namely the two resolutions of 6.3mm and 12.5mm, TLS was used to acquire points cloud data. The points cloud was processed and reduced with the “remove redundant points” function to check the size of the file. In the end, the points cloud was exported in image format to the navigation application. The optimal resolution obtained to scan a small indoor asset was 6.3mm resolution, even though the time to acquire it doubled the amount of time acquired by 12.5mm resolution. The higher resolution is not recommended for acquiring data on-site as the total columns of points across 80mm is only 21columns with a 3m distance from equipment to target. As a result, it is recommended to use 6.3mm to acquire a small indoor asset no further than 6m in the distance from the equipment. The user feedback concluded that the importance of the indoor asset navigation application is based on the point cloud data, and most of them were pleased to see such an application which can develop to help them in building management and maintenance. In conclusion, this study shows that the navigation application with points cloud data can improve building management and maintenance performance.