Point Cloud Conversion to 3D Modeling: The Roadway as it is
In the age of digitization, reconstructing the as-built condition of archaic buildings for construction companies and surveyors isn’t a tough task. Point cloud modeling has redefined the tasks and the continuously improving features of 3D modeling platforms like Revit or simple CAD such as AutoCAD, the work for surveyor and engineers has become easier.
Building Construction Design: Diversity and Complexity
When point cloud scanned data is gathered, the difficulty level of reading that data and converting the point cloud scans into 3D models depends upon the building type, its orientation, and density of building components. Construction companies face this challenge more often in case of commercial complexes, shopping malls, and hospitality buildings.
No two buildings will be the same. The HVAC systems layout, MEP connections, structural skeleton of the building, firefighting systems and many other aspects need to be modeled precisely during point cloud conversions to take accurate and informed decisions.
Other times, in addition to the complexity, it is required that parts of the facility are to be retrofitted or renovated while the remaining of the facility is still operational. Healthcare facilities projects often face this situation and are the most difficult to deal with.
Point Cloud Conversion: Going down the Road
Ideally, when the point cloud scans or the point cloud mesh when imported in BIM platforms like Revit, each object can be identified distinctly. It is usually because when the photos are taken with high definition scanners, they give a true color for 3D point cloud so that every element can be differentiated and an intelligent BIM model can be created.
So when the laser scans or the point cloud data is populated, it reads the intelligence within in form of motion data like in video games. It essentially reads using a number of scanners by translators and BIM companies can convert this into 3D BIM models.
At any time during the conversion, there will be millions of points being scanned during the scanning and more the density of points more will be accuracy in generating models. Usually, the distance between any two points on the cloud will be as low as 2-3 mm so that the generation of 3D geometry is easier and interpolation can be avoided to a greater extent.
Point Cloud Conversion: The Roadblocks
Once the BIM Company or the point could engineer initiates the conversion, usually there are more than one scans of the building that are to be studied so that every corner of the building is included for the scan. Now the older scanning to BIM technology posed challenges in detecting finer details from the scan especially while distinguishing two objects from one another when they are integrated into a single structure.
Point cloud to mesh helps in eliminating these challenges. By converting the data into a mesh, the engineer is ideally converting the point cloud data in an organized form and renders the scanned data. These characteristics are important especially when the scans are zoomed in and the details would still remain intact.
Secondly, when the scans are rendered, the properties of structural elements can be made known with better quality. The sagging or hogging of beams, its slope, curvature, type of wall, and its material etc. properties can be known with certainty. This would give the engineers to have an opinion with concrete backing and model accurately.
Point Cloud Conversion & Modeling: The Final Destination
Now, the point could that are obtained as inputs to the construction company or a BIM engineers is actually a raw output from the laser scanners like LiDAR or photogrammetry. They need conversion to mesh and finally, a data-rich intelligent 3D model that can warehouse engineering, geometrical and technical data for the facility under renovation.
Meshes are generated using a 3D solid modeling platform in a basic CAD or detailed BIM. Additionally, engineers today also use surface reconstruction methods that help in the development of accurate meshes.
These detailed 3D models warehouse the information right from the ground floor, its interiors, floor above it, to all the way till the coordination of each element and how they interact with each other in the building system.
Catch here is that the value that point could conversion to mesh and finally to the models is unparalleled. It addresses challenges that go way beyond the typical construction coordination issues. It turns a mere collection of point cloud scans into a highly organized information management model which can be leveraged for future use too.