# Automated Schedule and Cost Control Using
## 3 Methodology
### Methods
#### 3.2.2 Automated Schedule and Cost Control
Some of these columns failed to be recognized because of occlusions; hence they are colored yellow. Similarly, from Figure 4, it was observed that the object recognition results obtained from the scan on 20 January 2021, where the foundations were not recognized, as mentioned in the previous paragraph. Nevertheless, the second-floor slab showed modest progress in the schedule; hence they are colored green. While the second-floor slab is not yet fully constructed; therefore, they are colored blue. Three-dimensional object recognition is built mainly on the similarities between the attributes and properties in as-planned and as-actual models. Therefore, researchers used various approaches to recognize the 3D point clouds. Therefore, the case study findings and previous studies regarding object recognition results [17; 19; 37] are compared. The case study findings show a higher precision and recall than those presented by [17; 37]. However, it is in agreement with the findings reported by [19]. Figure 4: The object recognition results between models on 20 January 2021. Figure 3: The object recognition results between models on 25 December 2020. ### Schedule and Cost Control

The proposed system generates a user interface where the calculation of the progress tracking for schedule and cost can be measured. The user interface estimates the progress of schedule and cost based on the principles of EV using the budgeted cost of work scheduled (BCWS), Budgeted cost of work performed (BCWP), and Actual cost of work performed (ACWP). Figure 5 shows the progress tracking results for the scan acquired on 25 December 2020 using the schedule and cost of concrete work in the case study. Figure 5 also shows the total cost from unrecognized elements in BCWS, BCWP, and ACWP. However, as previously illustrated, the foundations were considered the only unrecognized elements in this case study. They must be included in the schedule and cost estimation because construction activities depend on the foundations' completion. In this case study, due to the 100% completion of the unrecognized elements (the foundations), BCWS is equivalent to BCWP as presented below Cost (5D) in Figure 5.

Table 5 demonstrates the results of the 4D progress for the case study, including the costs of unrecognized elements. Using the calculated SPI, the schedule performance of the whole project at chosen scans was determined. The results showed a fast-track project where the two scans were ahead of schedule, as the SPI was larger than one in both scans. Fewer studies were conducted to update the schedule automatically [15; 27; 37]. These studies mainly depended on the construction schedule to show the progress. Meanwhile, this paper demonstrates the automation of an updated schedule based on the visible recognized elements and their budget unit cost to calculate the schedule performance index. In addition, Table 6 demonstrates the results of the 5D progress for the case study, including the costs of unrecognized elements. The cost performance of the whole project was obtained using the calculated SPI. The results showed a saving project where the two scans were under budget, as the SPI was larger than one. To the author's best knowledge, this paper is the first to address the 5D assessment in the CPM domain integrated with BIM because previous studies indicated the lack in this field, as presented in [30; 31; 32]. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Scan Date** & **BCWS (S)** & **BCWP (S)** & **SPI** & **4D Performance** \\ \hline
25 December 2020 & 854973 & 868655 & 1.016 & Ahead \\ \hline
20 January 2021 & 888250 & 894171 & 1.007 & Ahead \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Result of the earned value (SPI) to determine the project’s 4D progress (Including cost from unrecognized elements). Figure 5: The proposed system’s user interface Calculation of SPI and SPI on 25 December 2020.