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IoT Predictive Maintenance using ML

In this scenario, we illustrate the example of using machine learning and IoT data pipeline to support predictive maintenance.

ML and other services/units

We use ML Units for BTS Prediction for:

  • create ML services by deploying ML models into a service
    • the service accepts requests from messaging systems (currently using AMQP)
  • using other units/services for emulating sensors
  • ML clients can take data from sensors, preparing data for ML requests and sending the requests to the ML service
    • Currently a ML client just reads pre-processing data from files. A developer can change the code to read data from MQTT (e.g., using our IoTCloudUnits) and to perform the data preprocessing