With advances in laser scanning technology, point cloud surveys of existing buildings provide highly detailed data to digitally model structures as 3D BIM for renovation, retrofit, or documentation projects. Converting raw scan data into intelligent Building Information Models unlocks immense value. This guide covers point cloud to 3D model conversion workflows, considerations, benefits, and tips for effective BIM Modeling from laser scan data.

Introduction to Generating 3D BIM Models from Point Clouds

Point clouds produced by laser scanning contain millions of surveyed 3D data points accurately capturing existing conditions. While immensely useful for visualization and measurement, point clouds lack intelligence and the parametric Modeling capabilities of BIM.

Converting point clouds into Revit or AutoCAD BIM models provides the best of both worlds – the accuracy of scan data combined with the intelligence and utility of a BIM model. This enables architectural documentation, clash detection, quantity takeoffs, maintenance planning, and more.

Understanding Point Cloud Data and Limitations

Point clouds are highly detailed but consist purely of geometric data points along with RGB values if captured with cameras. Point clouds alone lack:

• Parametric intelligence relating model elements
• Objects classified into doors, walls, pipes, etc.
• Non-geometric attributes like material types
• Relationships between points
• Clean geometry convenient for downstream uses

Converting point cloud scans into BIM models adds this missing object intelligence and clarity.

The Benefits of Converting Point Clouds to 3D BIM Models

By taking raw scan data into an intelligent BIM model environment, users gain:

• Parametric objects like walls that dynamically update when modified
• Semantic information like material definitions attached to objects
• Clean geometry optimized for clash detection and quantity takeoffs
• Relationships between objects, systems, and spaces
• Support for construction lifecycle uses like design, procurement, and facilities management
• Tools for model interrogation to extract insights

This unlocks far deeper application of scan data than point clouds alone.

Step by Step Point Cloud to 3D Model Workflow

Typical scan to BIM workflows involve:

1. Capturing multiple LIDAR scans with RGB data from set locations throughout the building.
2. Registering scans into a unified point cloud using target references.
3. Segmenting and classifying the point cloud into distinct architectural, structural, and MEP elements.
4. Modeling the main structural components like walls, floors, roofs within BIM software.
5. Adding MEP systems like HVAC ducting and piping networks to the BIM model.
6. Performing clash detection, validating model accuracy, and refining as needed.

The process requires both automated software processing and skilled manual modeling to build an accurate BIM model.

Software Tools Used for Converting Point Clouds to BIM

Specialized software helps process raw scan data and generate BIM models:

• Point cloud processing programs like Autodesk ReCap, Trimble RealWorks, and ClearEdge3D register, clean, and segment scan data.
• BIM authoring tools like Revit and AutoCAD facilitate actually modeling components based on point cloud geometry.
• Third-party scan-to-BIM plugins like EdgeWise and Pointsense expedite converting point clouds into intelligent Revit families.

Multiple software options help streamline this data translation process.

Key Modeling Considerations When Working from Point Clouds

Some modeling techniques help overcome point cloud limitations:

• Supplement areas with low scan detail with supplemental measurement.
• Reduce noise with smoothing while retaining key geometry.
• Generate closed, manifold geometry from open disjointed point data.
• Assign model objects semantic information like material types not captured by the scan.
• Simplify complex objects using design assumptions when needed.

Blending scan data with intelligent modeling decisions is vital for high quality BIM generation.

Applications of BIM Models Generated from Point Cloud Surveys

Some top uses for point cloud-based BIM models include:

• Creating highly accurate as-built BIM models for renovation projects.
• Building Information Modeling to document existing buildings.
• Comparing as-built point clouds against design BIM models.
• Planning safety upgrades like new fire sprinkler systems in old buildings lacking drawings.
• Virtual inspections and spatial clearance analyses.
• Preserving heritage buildings in a digital 3D format for posterity.

The applications are vast for modernizing aging structures.

Benefits Provided by Point Cloud Converted 3D BIM Models

Converting point clouds to BIM delivers significant advantages:

• A highly accurate 3D model of existing conditions for visualization and measurement.
• Faster model creation compared to completely manual BIM modeling.
• Extracting precise quantities and insights from the intelligent model.
• Support for the full construction lifecycle from design to turnover and facilities management.

For aging or undocumented buildings, laser scans breathed new life into BIM processes.

Challenges to Modeling BIM from Point Cloud Data

While transformational, the point cloud to BIM process poses challenges:

• Considerable skill needed to build BIM models from often messy scan data.
• Large scan file sizes that strain computers and slow workflows.
• No automated way to convert point clouds into parametric BIM models.
• Extensive manual clean-up of scan artifacts and holes in the resulting model.
• Difficulty capturing certain geometry like reflective or rapidly moving objects.

Continual software improvements help streamline this complex process over time.

Tips for Effective Point Cloud to 3D Model Workflows

Some best practices for smooth point cloud to BIM translation:

• Carefully plan site scanning coverage to capture all required architectural and MEP geometry.
• Use target references or traverse surveys to accurately register scan data.
• Model sections iteratively in manageable pieces for cleaner results.
• Focus intensive manual cleanup efforts only on critical BIM areas, letting software handle bulk.

The combination of robust software and strategic modeling technique makes point cloud to BIM achievable at scale.

Conclusion – Unlocking New Utility From Existing Conditions Data

In closing, converting point clouds from as-built laser scans into intelligent 3D Building Information Models unlocks tremendous new opportunities for working with existing structures through construction’s most powerful digital tool – BIM. With the right planning, software, and skill, organizations can cost-effectively build accurate BIM models from point cloud scans of aging assets originally created before the advent of digital documentation. Contact a reputable scan-to-BIM service provider to explore how this transformation process can upgrade your current building portfolio into a powerful data-driven asset.