• Connected AI – automated enhancement with more cameras
    Addition of cameras will automatically improve positioning without explicit reconfiguration by the installer
  • Flexible and Minimal installation and maintenance requirements
    The installer only needs to ensure the camera is looking at the intersection and provide its approximate GPS location. It can use existing cameras
  • Self Calibrating
    The system will calibrate itself by automatically identifying visual cues for positioning, requiring minimal input from installer
  • Self Healing
    Long-term camera movements, misalignments and change in pose (e.g., due to wind or vibration) will be automatically corrected

Full Package Hardware

AI vision Cube

AI Vision

Full Package Software

  • CAPLOC precision localization software stack for smart infrastructure
  • CoVIsion cooperative perception software packages for ADAS/vehicles.

AI Vision Cube
out of the Box Solution

Product Features
  • Calibration and CAPLOC Software Stack
  • Versatile sensor interfaces: Camera, Lidar, Radar
  • Connects to RSU or to Vehicle Computer



Patent pending technology

  • achieves highest object recognition accuracy
  • Allows use of lower cost sensors and increases range of sensing
  • UCF patent pending IP licensed

Innovative Cooperative technology

between vehicles, or vehicles and nearby infrastructure

  • achieves higher accuracy at very low data transfer rates
  • Allows localization in GPS limited areas or indoor

Single vehicle systems achieve

  • high accuracy through spatio-temporal sensing
  • Allows self-localization with recorded maps or indoor.

Our Core Technology: Connected AI Vision,  
CAPLOC (camera based)

Disruptive Innovation

  • high accuracy AI Vision achieved through connectivity (IP)
  • versatile AI vision software for autonomous vehicles and smart environments with the highest accuracy

Market Disruption

  • Commoditize Hardware: Shift complexity, and value, from hardware to software
  • Reduce hardware requirement and cost (e.g., LiDARs for AVs) through smarter algorithms
  • Make lower resolution LiDAR a viable choice for AVs
  • Rely on the power of GPU algorithms to compensate for sensor deficiency
  • A network of lower cost sensors is superior to single costly sensor