## 7 Conclusions  
This work illustrates the significant role that scanning parameters--such as scanning distance, speed, angle, number of passes, and lighting--play in the accuracy of scans conducted with the iPad Pro's LiDAR. Despite this importance, no systematic methodology for defining the optimal levels of these scanning parameters is presented in the literature. To address this gap, this study proposes the application of [PERSON]'s orthogonal arrays to identify the critical scanning parameters and their optimal levels. The analysis of three objects with varying complexities revealed that the most important scanning parameters are a short distance from the object, have a fast scanning speed, and natural lighting. The selected optimal levels were then used to scan a heritage structurefeaturing different structural elements and cracks. The results obtained from scanning this structure demonstrate how the chosen optimal levels for the scanning parameters significantly reduce measurement errors in the geometry of the scanned model compared to randomly defined parameters. In terms of practical applications, the findings hold significant promise for conservation professionals and researchers who often face financial constraints. The use of easily accessible devices, such as the LiDAR of the iPad Pro, opens up new possibilities for institutions with limited resources to engage in high-quality documentation efforts. However, the study is not without limitations. One major constraint is the iPad Pro's limited range and reduced accuracy when capturing complex geometries or finer details in intricate heritage structures. The LiDAR sensor's 5-m range and relatively low point density, especially compared to professional-grade terrestrial laser scanners, remain limitations that affect its ability to capture highly detailed or large-scale heritage elements. Additionally, environmental factors, such as lighting conditions and surface reflections, still pose challenges, which were controlled to some extent in this study but may not be easily manageable in all field conditions. Future research should address these limitations by exploring improvements in both the hardware and software associated with mobile LiDAR technologies. Specifically, further studies could investigate enhanced calibration methods to optimize accuracy when scanning complex geometries and under varying environmental conditions. The integration of multi-sensor data fusion, combining LiDAR with photogrammetry or other technologies, could help overcome some of the inherent limitations of using a single scanning technique. Moreover, future studies could extend the scope of preliminary tests to include objects directly related to cultural heritage, such as architectural elements (e.g., columns, beams) and decorative artifacts. Focusing on these specific targets, the methodology will be better aligned with its intended applications in heritage conservation. In addition, future studies could extend this approach by incorporating the influence of different mesh generation software, introducing a new parameter (mesh software). This influence could potentially introduce data loss or distortions affecting the models' performance. Finally, testing the applicability of this technique in interdisciplinary contexts--such as archaeology or environmental monitoring--would expand the utility of mobile LiDAR scanning, offering further contributions to diverse fields that require affordable, accurate 3D documentation solutions. Conceptualization, E.A. and J.A.L.-G.; methodology, E.A., A.M. and J.A.L.-G.; software, E.A. and A.M.; validation, J.G.-A., A.M. and F.L. ; formal analysis, E.A., A.M. and J.A.L.-G.; investigation, E.A., A.M., J.G.-A., F.L. and J.A.L.-G.; resources, J.G.-A. ; data curation, E.A. and A.M.; writing--original draft preparation, E.A. and A.M.; writing--review and editing, J.G.-A., F.L. and J.A.L.-G.; supervision, J.A.L.-G.; funding acquisition, J.G.-A. All authors have read and agreed to the published version of the manuscript.