The Voxelmaps Insight Platform (VIP) delivers a fully automated pipeline for processing LiDAR data and high-resolution imagery to extract assets, features, and detailed 3D volumetric data from complex datasets.

Leveraging advanced deep learning and AI algorithms, VIP performs semantic segmentation in 3D, enabling more accurate and intelligent feature recognition beyond traditional 2D analysis. This voxel-based system is data agnostic—capable of ingesting inputs from satellites, aerial data collection services (both manned and unmanned), mobile mapping sensors, and even wearable devices for precise, ground-level terrestrial mapping.
Below is a list of some of the automated data processing we offer:
Co-registration of LiDAR point Clouds
Sensor Fusion of LiDAR, Camera, GNSS & IMU data
Position Accuracy Enhancement through SLAM scene alignment for 3D data
Automated Asset and Feature Extraction of Road and City Scenes
Automated Measurements and Attribute Creation of Road and City Scenes
Indoor LiDAR data processing & Automated Feature Extraction
Deep Learning Based People, Vehicles & Moving Objects Recognition, Extraction and Removal
Automated Privacy Processing – Blurring of People Faces and Number Plate data from Image and Video Data
4D Spatial Data Processing for Change detection in Road and City Scenes
We have extensive experience of exporting the data into many different formats including, but not limited to: Shape, NDS, GeoJSON and XML. In addition to the automated data processing workflows listed above, it is possible for Voxelmaps to customize its algorithms and pipelines to extract other types of data.
The Voxelmaps Insight Platform offers cost-effective, affordable, and accessible tools to collect and utilize digital data to improve business processes, identify potential problems and create new opportunities for organizations within many different industries. Please feel free to reach out if you would like to see what is possible with your data set.

To learn more about our LiDAR mapping services contact us today!

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