Pointly’s Powerline Classifier uses AI to automatically classify and analyze 3D point cloud data from powerline corridors. It transforms large LiDAR datasets into structured and actionable geospatial information while significantly reducing manual processing effort.

The classifier can automatically identify key infrastructure and environmental classes including transmission towers, conductors, ground, vegetation, buildings and other relevant objects. Models can also be customized to distinguish specific components such as conductor types, earth wires, insulators and tower structures.

Beyond point cloud classification, Pointly can automatically derive additional information such as conductor lines, tower positions and heights, attachment points, vegetation clearances and potential encroachment risks. Selected assets can also be extracted as vector data for further use in GIS, CAD and asset management workflows.

Pointly supports both pretrained models for rapid processing and custom AI models optimized for specific datasets, sensors and class requirements. Processing can be integrated through the Pointly platform or API and can also be deployed locally for projects with strict data security requirements.

Key capabilities

• Automated AI based powerline point cloud classification
• Tower, conductor, vegetation and ground detection
• Custom classification catalogs
• Conductor and infrastructure vectorization
• Tower position and height extraction
• Wire and insulator attachment point extraction
• Vegetation clearance and encroachment analysis
• Processing of large LiDAR datasets
• Platform and API integration
• Local processing options