Commercial UAV Expo Europe  

September 3-5, 2024  •  Caesars Forum  •  Las Vegas

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Delair Launches Automatic LiDAR Classification Application

New feature in visual intelligence platform helps scale operations and gain up to 90% in productivity compared to manual methods.

Delair launches a new solution that enables anyone with LiDAR data to use the visual intelligence platform to rapidly and automatically classify LiDAR point clouds. In, machine-learning processes deliver automatic point cloud classification, a major step forward for automatic data recognition and infrastructure inspection in multiple industries including construction, utilities, geospatial applications.

Why do we need to classify point clouds?

Point clouds are built by aggregating georeferenced points with x,y,z values and position attributes. In order to be analyzed, point clouds have to be classified according to elevation. Classification is what makes it possible to build detailed and structured digital twins of an infrastructure and its surroundings, with a clear differentiation between the different objects in the digital model.

LiDAR point cloud of a distribution power line in 

Easily manage your data and classify your LiDAR point cloud using’s machine-learning algorithms is a visual data warehouse that aggregates imagery and georeferenced data, and organizes it into a structured asset-oriented database.

Trained A.I. and machine-learning algorithms in automatically classify LiDAR point clouds to generate highly detailed digital twins of an infrastructure – power line, construction site, pipeline, … – and identify even the smallest objects. Large amounts of LiDAR data – up to 300 km (190 miles) per day (or 300 km2/ 120 square miles) – can be rapidly managed and classified, and the application delivers fully automatic classification of 5 standard classes: poles, conductors, ground, buildings and vegetation (low, medium, high). With a dedicated AI algorithm training  process, additional classes can be added to meet the needs of a specific project.

Digital twins can then be rapidly and repeatedly analyzed in to transform the asset data into actionable business insights and help make right decisions here and now, as well as predict future developments of the asset.

Automatically classified LiDAR point cloud of a distribution power line in a rural area in

How does it work ?

1- Upload your data: create your project on, upload your .las file and choose your coordinate system

2- Visualize your data: get a 3D view of your LiDAR survey and fly virtually over your assets

3- Run the Automatic LiDAR classification app with a click: get your classified point cloud, visualize your assets and surroundings, export your classified point cloud.

In, all the data is aggregated and processed in the cloud, removing the need for high performance hardware infrastructure investments. Digital twins can be visualized in the cloud from a standard web browser to provide access to data anytime from anywhere, and a broad range of Industry-specific analytics are available to get more value out of the data.

Automatically classified LiDAR point cloud of a distribution power line in an urban area in
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