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Smart City, an Edge-to-Core Data Story


The full source and instructions for this demo are available in this repo

In this demo, we show how to implement this scenario:

  • Using a trained ML model, licence plates are recognized at toll location.
  • Data (plate number, location, timestamp) is send from toll locations (edge) to the core using Kafka mirroring to handle communication issues and recovery.
  • Incoming data is screened real-time to trigger alerts for wanted vehicles (Amber Alert).
  • Data is aggregated and stored into object storage.
  • A central database contains other information coming from licence registry system: car model, color,…​
  • Data analysis leveraging Presto and Superset is done against stored data.

This demo is showcased in this video.