## 4 Conclusions  
As the literature indicates, there is a shortage of studies in the area of construction management that assesses close-range photogrammetry, especially that associated with using smartphones as the data collection tool. Thus, this paper presented a study that assessed the potential of using a smartphone as a data capturing tool based on the quality and geometrical accuracy of its photogrammetric outputs compared with a compact camera. The quality and geometrical accuracy assessments were conducted based on various criteria that were selected according to previous assessment studies and photogrammetric software guides.  
The results reveal that the smartphone data (SP) were associated with higher lens distortion compared with the digital camera data (DC). The RMSE of the 3D reconstruction associated with SP was found to be higher, almost twice that of the DC. On the quality level, the SP's sparse clouds were associated with a higher noise level compared with the DC's clouds. Additionally, the DC's dense clouds had a higher points density, nearly 3 times the density of those of the SP. This difference resulted in a better geometrical detail representation and a higher mesh quality with the DC's models. The DC's final textured models had a higher quality and a better photorealistic appearance compared with the SP's. However, the SP's dense clouds and textured models were of acceptable quality. The processing time and memory utilization parameters of almost each processing step in the photogrammetric workflow were generally less with the SP.  
The geometrical accuracy assessment revealed the higher accuracy of the DC's models in estimating the specimens' surface areas and volumes compared with the SP's models. Nevertheless, the SP's models resulted in surprisingly accurate geometrical estimations despite the relatively inferior specifications. The volumetric estimation error ranged from 0.37% to 2.33% for DC and 0.67% to 3.19% for SP. For surface area, the error ranged from 0.44% to 0.91% for DC and 0.50% to 1.89% for SP.  
These findings confirm the reliability of the self-calibration approach employed in this study for both cameras. They also indicate that smartphones can be utilized directly for acquiring on-site photogrammetric data for 3D modeling and measurements extractions for construction management applications (e.g., materials quantity take-off and progress measurements). However, the findings of this study are limited to smaller quantification applications since it was conducted on relatively smaller construction elements/materials. Therefore, future research needs to be conducted for larger construction elements (e.g., facade, building structures, etc.) or for tracking ongoing construction activities (e.g., earthmoving operations, excavation tasks, etc.). Furthermore, the study only evaluated two types of cameras (i.e., Nikon-D 3300 and Huawei Mate 10 life); therefore, the authors recommend conducting similar studies for different types of cameras (i.e., smartphones with different camera specifications and different compact camera brands), thus providing more comprehensive comparisons and full assessments. Additionally, future research can be conducted to quantitatively examine the relationship between the camera specificationsof smartphones (megapixels, lens size and distortions, sensor size, and focal length) with the reliability of the resulting 3D data.  
Conceptualization, W.S. and A.A.; methodology, W.S.; software, W.S.; validation, W.S. and A.A.; writing--original draft preparation, W.S.; writing--review and editing, W.S. and A.A.; supervision, A.A. All authors have read and agreed to the published version of the manuscript.  
This research received no funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors would like to thank King Fahd University of Petroleum and Minerals for the research facilities and support that contributed to carrying out this research.  
The authors declare no conflict of interest.