# Using Dynamo for Automatic Reconstruction of BIM Elements from Point Clouds
## 6 Conclusions  
The optimization of geometric reconstruction and BIM modeling from point clouds can happen in several stages of the scan-to-BIM process through different methods and tools. This research explored ways to circumvent the known problems of this process and developed optimization approaches that can be performed both in the point cloud manipulation steps and in the geometric modeling itself. This article presented a case study focused on developing computational algorithms using Dynamo's visual programming language for problem-solving and process optimization in the scan-to-BIM workflow. The results of the models obtained using the algorithms were quite positive. The models presented a high level of precision and accuracy. They were also created as BIM elements in their correct Revit categories and not simply generic geometric models that do not interact correctly within the BIM workflow. The process was not time-consuming, which significantly contributed to simplifying and making the scan-to-BIM work more dynamic. The result of this research was the development of the following algorithms to be used with Dynamo and Autodesk Revit:  
* Topographical surfaces modeling algorithm. * Rectangular or square profile structural columns modeling algorithm. * Rectangular or square profile structural beam modeling algorithm. * Slabs, structural floors, and roof modeling algorithm. * Regular walls (non-curved) modeling algorithm. All codes brought gains to the process compared to traditional methods and approaches. In addition, the computational processes, and the use of the programming environment as a tool to overcome problems and challenges, proved to be highly efficient. It is possible to use Dynamo to develop future solutions by exploring other types of elements and problems in different design phases. The contributions that the algorithms developed in this study brought were as follows:  
* Creation of models with higher precision and accuracy than traditional methods. * Low time consumption, 25% faster than the manual approach. * Automatic measurement of element dimensions and automatic creation of types in selected families. * Automatic detection of vertical, horizontal, and rotational deviations in columns and beams. * The use of native Revit elements and families without the need to use generic external 3D models. * Possibility of integrating the created elements into the BIM workflow without any incompatibility. * Automatic modeling without using other external software or commercial plugins available on the market. The research results discussed significantly contribute to the wider adoption of automation tools in the AEC industry for scan-to-BIM. The developed techniques streamline the BIM modeling process by reducing manual labor, which is often time-consuming and prone to inaccuracies. The automation not only enhances the precision and speed of converting point clouds into detailed, usable BIM models, but also addresses common challenges such as modeling geometrically complex or irregular forms. Moreover, this research highlights the potential for a broader application within the industry, encouraging the uptake of scan-to-BIM techniques. This can lead to improved collaboration and efficiency in building projects, particularly as the fidelity and detail of automated models increase. The case study utilized demonstrated the practical implementation and validation of these techniques, likely encouraging further exploration and adoption of such technologies by professionals seeking similar benefits in accuracy and efficiency.