*4.2. Discussion of Results*

Based on the proposed method, the Z planes were inserted at 5 cm interval from 1 cm to the height of the high formwork. Next, the lines representing the individual poles or tubes were generated. Then, the coordinates of the cross points were input the ANN model. Both longitudinal and transverse spacing of pole and lift height (the distance between two neighbouring ledgers) were checked. Moreover, the perpendicularity of pole and levelness of ledger were inspected. In addition, the angle of the diagonal bracing of the high formwork were checked. The standard error was calculated between real value and estimates. The standard error can be calculated in Equation (9).

$$\text{SE} = \sqrt{\frac{\sum \left(Y - \mathbf{Y}'\right)^2}{N}},\tag{9}$$

where *Y* is the real value, *Y* is the estimated value, and *N* is the number of points to estimate. The overall accuracy is acceptable and the errors fall within the allowable tolerance range. The results are summarized in Table 7. The results indicate that the accuracy of the developed GA-ANN model is satisfied at the millimetre level. It can generate reliable results in real applications.

**Table 7.** Summary of the predicted error by using the proposed method.


Note: Am indicates the angle of diagonal bracing.

The purpose of the validation is to examine the performance of the proposed approach dealing with real problems. Moreover, short range (about 10 m), simple scanned area, and scanning from one position can reduce errors. Results of the validation indicate the proposed method can detect and locate defects. Optimistically, it is capable of providing accurate measurements at the magnitude of the millimetre level. Based on the outcomes, the proposed method provides an effective tool for installation quality inspection for high formwork.

Based on the cost and time evaluation, the proposed method can provide an effective tool for quality inspection of a high formwork. The scanning time used for the inspection at every station was only twenty minutes, which suggests the superiority of the adoption of TLS in terms of both cost and time when compared to common methods. For example, a GNSS-based method, which recently was suggested for use in structure monitoring and inspection, has an error at the magnitude of the centimetre level, and requires extensive calculation and processing [76,77]. With such an error budget, it is unacceptable for installation quality inspection for high formwork. Moreover, to improve accuracy, it usually requires the addition of more stations which will significantly increase operation costs. Other methods, like unmanned aerial vehicle (UAV) imagery, are also recommended as an effective tool for installation quality inspection for high formwork. However, based on previous studies [78,79], it has average error of about 15mm. Moreover, it requires sophisticated processing to extract the required information from the raw imagery. In addition, and most importantly, considering factors such as registration errors, missing data or mixed pixels might cause the misidentification of important elements or increase errors in the measuring of the dimensions of high formwork.

Without the use of TLS, to safely conduct quality inspection in a cost- and time-effective manner, and with acceptable accuracy, would prove extremely difficult and labour-intensive. Moreover, the data accuracy of TLS can be improved with the following suggestions: (1) conduct the scan without impacting the line-of-sight; (2) increase scanning resolution; (3) increase the number of scans; (4) scan the high formwork from all faces; (5) widen the range of scan stations.
