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Background

Detecting damaged wheels and other issues that may occur during heavy train transports. Need for advanced edge analytics and sending data to the cloud for historical usage and AI-training. Global control and management of deployed edge software.

Prerequisites

Remote locations and bandwidth constraints require local buffering (store data if/when the devices lose connectivity). Streaming sound frequency analysis with large volumes of data to 3rd party service systems and maintenance programs.

Solution

Crosser Node deployed in a digital box connected to the crossing:
  • Streaming sound frequency analysis algorithm deployed in a regular data flow
  • Integration to Crossing execution system and notification system
  • Sending data to cloud service for AI training and storage
Crosser Cloud:
  • Customer organization set up with roles
  • Resources library setup

Try Crosser For Free

Start innovating today. How it works:

  1. Get an account
  2. Log in and start designing your flows in the sandbox
  3. Download the Crosser Container to your local test node
  4. Test with real data