Classified Point Cloud: The Future is Intelligent

Team ClearEdge3DUncategorized

EdgeWise

Much effort is made of extracting a point cloud’s inherent value. For example, EdgeWise interprets point cloud data, identifies building elements and creates corresponding model representations in Revit, AutoCAD, etc. Hardware innovations strive to add more value to the point cloud as well, including capture of color, reflectivity and other information associated with any one point. It’s important then, for us to consider the future of the point cloud, its applications, and how it aligns to a Building Information Modeling (BIM) value chain.

The Point Cloud of the Future

Imagine, if you would, a single point within a point cloud that’s enriched with classifications beyond location, color and reflectivity. In addition to those attributes, the classified point knows that it’s a metal stud wall with 5/8” gypsum board, it knows the collection of other points that are part of the same wall, it knows it’s fire-rated for one hour and it knows it’s relation to itself within a design model. Would that be valuable?

Classified Point Cloud

Classified Point Clouds Bridge the Gap

If point clouds are a representation of existing conditions, then classified point clouds are a bridge between the information-rich design model and actual as-built conditions. It’s not a stretch to imagine that classified point clouds and intelligent design models will become indistinguishable complements to one another within BIM enabled workflows; the former serving to multiply and extend the value of the latter.

The Point Cloud Revolution is Near

This future may not be that far off in the distance. We see pieces of the puzzle that could complete the vision taking shape today. Points within Autodesk ReCap are smart enough to know if they fall on a cylinder or plane with other points. Our own EdgeWise automatically identifies that a set of points belong to an ASME standard 4” pipe, for example.

Current technology makes it relatively easy to create a design model or (separately) an as-built model. The missing piece of the puzzle, however, remains to be the intelligent association, comparison and interaction between design model and as-built conditions. What would a Construction team do if they could scan a site at key milestones to identify missed or out-of-tolerance structural elements before an error triggers change orders, shutdowns and expensive rework? It’s truly empowering. Surely, the industry would realize a much more robust definition of building information modeling. And all because of those classified point clouds…

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