Few latest decades have seen rapid growth in the application of LiDAR in various industrial domains. LiDAR sensors become more and more available and currently can be fit on any device from a drone to a vehicle performing high precision data collection quick and easy. Yet, the most challenging and time-consuming task is to process the data accurately and deliver valuable insights to the final customer.

EOS - is the one to undertake the mission of interpreting and analyzing big data for a diversity of your needs. From now, with the advanced algorithms from our data scientists team, you are able to get the most precise outcome.

Precise automated LiDAR solutions for your business

Solutions for LiDAR Data Processing Companies
  • Buildings Modelling Automation
  • Rooftops Modelling Automation
  • Urban Change Detection Automation
Solutions for City Planners, Augmented reality & Gaming
  • Urban Modelling and Analytics for Smart Cities
  • Detection of City Changes, update of an urban building inventory database
  • Robust 3D Visualization of the urban environments. Augmented Reality 3D City Maps
  • Estimation of the Shadow Cast and Reconstruction of Sunlight Direction
  • Population estimation in city suburbs, and throughout rural territories
Solutions for Asset Management, Energy, Agriculture
  • Urban/Commercial asset inspection
  • Topographic analysis and prediction of soil properties in agricultural landscapes
  • Monitoring of tree grove structures
  • The estimation of the solar potential of buildings
  • Security real-time perimeter monitoring
  • Estimation of environmental risk assessment for insurance policy

Automated Feature Extraction

We detect built structures and produce accurate 3D urban models from raw LiDAR data Point Clouds in a fully automated mode. As a result, raw point cloud input data is transformed into 3D vector models with a high level of detail.

Key use cases:

  • Urban 3D feature
  • Natural and human environment
  • 3D urban modeling
  • Urban Environment
  • Detailed model preview

Urban Change Detection

The system provides monitoring of city architectural changes over a selected period of time as an automated comparison and analysis of two LiDAR Point Clouds. This solution detects locations of changes in positions and shapes of buildings as 3D models with information about these changes.

Processing agriculture before
Processing agriculture after change detection
City change detection in the block, district, and whole city scopes over different periods of time
The exact location of changes
Detailed geodatabase of urban changes
Changes statistics

Topographic Modeling & Analysis

The system builds a Digital Elevation Model that represents the bare earth terrain of a selected area, which is essential while managing various types of projects. It helps to visualize the contours accurately and precisely and get almost the real picture with all the natural and man-made objects within the area.

Digital Elevation Model
Watershed delineation
Aspects, Slopes, Viewsheds
Channel networks
Contouring, 3D contouring

Data Formats Supported

Input data

  • LAS (LAZ) 1.0 -1.4
  • .SHP vector file
  • etc.

Output data

  • GeoTIFF
  • .KML/.KMZ
  • .Obj

All files within input datasets should have the same coordinate reference system

Point density should be more than 3-5 points per square meter

LIDAR based surveillance system

Security real-time perimeter monitoring

Delivers software solutions for state border surveillance, commercial and civil asset management, and security monitoring

The surveillance solution is highly effective for any land monitoring and may be deployed in the worst conditions for visibility including dust, smoke, fog and more. The software can be employed as a stand-alone monitoring system or together with other existing surveillance techniques such as a Video Surveillance System.

surveillance info
Benefits of the LiDAR based surveillance system
  • Implements real-time automated 3D data processing:
    • Location of the detected features with 20 cm accuracy;
    • Depiction of speed, size, and the direction of a feature movement;
    • Ability to predict next movement probabilities;
  • Provides effective and high awareness in reduced visibility (Darkness, Duststorm, Thick Fog, etc.);
  • Outlines scenarios based on defined time, zone, type of the feature;
  • Allows to store only a relevant part of the surveillance video.
Real-time information stream
  • Intrusion allocation;
  • Feature size and dimensions;
  • Feature speed and direction;
  • Cameras suggested zoom;
  • Feature type and attributes.
Intrusion detection parameters
  • Accuracy of object location +/-20 cm;
  • Detection delay < 0.3 sec.
  • Accuracy of object size +/-20 cm;
  • Object speed 0.1 ... 10 m/s;

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