# Scan to BIM Mapping Process Description for Building Representation in 3D GIS
## 6 Prototype Development and Performance Analysis
### Results Analysis  
Through the SBMD method, even if the type and characteristics of the input dataset are changed, only JSON, which is a text format, needs to be modified so that the process can be easily reused and expanded.  
For the developed SBMD test, an ALS LAS dataset, including 5,067,019 points, was used. As a result of SBMD execution, all 178 buildings with attribute information included in the scan data were automatically generated (Figure 7).  
The execution time for 3D building creation was 71 s (Intel i9, 32 GB, GPU memory 8 GB). The SBMD process saved the coordinate system information necessary for GIS mapping, along with SHP, GeoJSON, and the IFC file during the Scan to BIM conversion, so the result could be visualized in a GIS program such as QGIS in Figure 7.  
For the analysis, a comparison between manual modeling using Revit and the SBMD execution time was performed, as shown in Table 4. For the comparison, an engineer with more than 7 years of experience in Scan to BIM engineering measured the BIM modeling time using Autodesk Revit, and the SBMD method's operation time with the generated information was measured.  
The indicators were defined as the Tm (manual work time), Ts (SBMD execution time), Am (area by manual modeling), As (area generated by SBMD), Vm (inputted vertices by manual), and Vs (vertices generated by SBMD).  
As a result, 2.26% fewer polygon areas (Error) in the manual-generated footprint were entered compared to the SBMD, 110.21% AoI (Amount of Information ratio) improved, and the generation speed (SBPm) was 23.7 times higher (Table 5).  
Figure 7: Building information list generated by SBMD.  
The manual operation times were compared according to the number of vertices in the footprint polygons. As a result, it was confirmed that, as the number of polygon vertices to be input increased, the variation in the working time increased (Figure 8). Figure 8 shows that, the larger the scan data, the more the quality of footprint generation depends on the modeler's experience.  
The SBMD method can be automated by connecting the algorithm modules required for footprint and BIM object generation, and it can deal with these problems more effectively because it can adjust the exposed model parameters according to the characteristics of the scanned dataset.  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Indicator** & **Manual Modeling** & **SBMD Execution** &
\begin{tabular}{c} **Difference** \\ **(SBMD—Manual)** \\ \end{tabular} \\ \hline (a) Operation Time Tm, Ts & 1896.13 (31.60) & 80.00 (1.33) & 1816.13 (30.27) \\ \hline (b) Buildings footprint area (m\({}^{2}\)) Am, As & 66,014.45 & 64,524.50 & \(-\)1490.95 \\ \hline (c) Vertex count Vm, Vs & 333 & 367 & 34 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Performance analysis of the SBMD compared to manual work (unit = second).  
Figure 8: Manual operation time analysis for footprint generation in the Scan dataset (\(x\)-axis = vertex input count about each building footprint’s polygon, \(y\)-axis = second).  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Indicator** & **1 st Factor** & **2 nd Factor** &
\begin{tabular}{c} **Difference** \\ **(SBMD—Manual)** \\ \end{tabular} \\ \hline (a) Error ((As \(-\) Am)/Am) & \(-\)1490.95 & 66,014.45 & \(-\)2.26\% \\ \hline (b) Aoi (Amount of  Information ratio = Vs/Vm) & 367 & 333 & 110.21\% \\ \hline (c) VTm (Vertex input Time,  Manual = Tm/Vm) & 1896.13 & 333 & 5.69 times \\ \hline (d) VTA (Vertex input Time,  Automatic = Ts/Vs) & 80 & 367 & 0.22 times \\ \hline (e) SBPm (Scan to BIM  productivity about manual  input = Tm/Ts) & 1896.13 & 80.00 & 23.70 times \\ \hline \hline \end{tabular}
\end{table}
Table 5: Error and information amount analysis of the SBMD compared with manual work.