# Simplified Scan-vs-BIM Frameworks for Automated Structural Inspection of Steel Structures
## 2 Literature Review
### Scan-vs-BIM in Construction
Their approach involves aligning the As-Planned 3D models with the As-Built point cloud data to identify and retrieve structural components within the scanned environment. This method was validated through laboratory experiments, demonstrating efficient and robust retrieval of 3D CAD objects from point cloud data. Additionally, they showcased how the approach could \begin{table}
\begin{tabular}{c c c} \hline \hline
**Level of Detail (LOD)** & **Tolerance (mm)** & **Resolution (mm)** \\ \hline Level 1 & \(\pm\)51 & \(152\times 152\) \\ Level 2 & \(\pm\)13 & \(25\times 25\) \\ Level 3 & \(\pm\)6 & \(13\times 13\) \\ Level 4 & \(\pm\)3 & \(13\times 13\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Point cloud quality definition introduced by GSA. facilitate automated construction progress assessment by comparing the planned models with the actual construction status [8]. [PERSON] and [PERSON] [20] proposed a 3D laser scan collection methodology for data acquisition for on-site dimensional inspection of piping systems in industrial plants. They proposed a Scan-vs-BIM framework with Random Sample Consensus (RANSAC) that performs a comparison function between the collected As-Built 3D point cloud and As-Planned 3D CAD. [PERSON] et al. [21] proposed the basic principle of project progress evaluation by applying the Scan-vs-BIM concept through 3D point cloud data and 4D parameters of BIM. As-built point cloud and As-Planned BIM comparison improves the efficiency and productivity of construction project management. They found that the Scan-vs-BIM framework could monitor the overall project status, including productivity analysis, progress, and quality verification, and easily identify issues and predictable engineering tasks. [PERSON] et al. [22] conducted a study to secure an accurate precast concrete model by applying the Scan-vs-BIM methodology in a Virtual Trial Assembly (VTA) environment. They developed an automated modeling approach to obtain As-Built point cloud models. The traditional Scan-vs-BIM method involves constructing a mesh by projecting to the unit plane (xy, yz, and xz planes). [PERSON] [23] developed an algorithm to increase the accuracy of point cloud processing and improved the accuracy of the Scan-vs-BIM framework by assessing the pipe axis plane of the As-Built point cloud data itself and projecting it there to implement a mesh. In conclusion, 3D laser scanning and the Scan-vs-BIM framework have demonstrated significant promise in enhancing construction project management, structural integrity assessment, and quality control. The integration of these technologies into the construction industry facilitates the transition from manual, labor-intensive evaluation methods to automated, data-driven approaches. However, the approach of the Scan-vs-BIM framework is still difficult to scale for real-time analysis. The reason is that the traditional framework comparing the As-Built scan and As-Planned BIM takes a long time to apply in real time and uses a lot of memory due to data transformation. Therefore, the existing methods for Scan-vs-BIM need to be improved to be suitable for real-time analysis [11].