The as-built building information model (BIM) has a huge potential for enhancing the efficiency of building and maintenance operations. To facilitate existing-structure data acquisition for the as-built BIM, a terrestrial laser scanner, which is fast, simple to use, and yet highly accurate, is widely employed. However, as-built BIM creation of building interiors using scanned point clouds incurs critical difficulties: the complex design of indoor structures, not to mention obstacles, necessitates time-consuming manual operation and resultantly huge data sizes, which often leads to system slow-down or failure. To manage this problem, most of the recent and current research has looked to full automation; yet facility management personnel still rely on traditional field measurements because their qualitative results can only be obtained under ideal conditions or with some errors. Alternatively, in this paper, a more practical semi-automatic methodology for improved productivity of as-built BIM creation with respect to large and complex indoor environments is proposed. The proposed approach produces three-dimensional (3D) geometric drawings through three steps: segmentation for plane extraction, refinement for removal of noisy points, and boundary tracing for outline extraction. The experimental results for two test sites, a relatively simple corridor and a complex atrium, showed a high data-size reduction rate: to 3.8 and 4.3% of the original sizes, out of 51.5 and 111.5 million points, respectively. Based on the automatically produced geometric drawings and the remaining points, manual as-built BIM creation was conducted. Using the extracted lines as guides, each object and its relationship were more easily identified and modeled. At the same time, the great reduction in the point clouds' data sizes enabled the modeler, using the BIM software, to efficiently manipulate the geometric drawing without system slow-down or failure. The proposed approach was shown to be a potentially effective means of improving productivity and reliability in complex indoor as-built BIM production.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Civil and Structural Engineering
- Building and Construction