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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