Real-time massive data analysis

Context summary

ThinkR was contacted in order to set up a tool to monitor the watertightness of a fleet of refrigeration installations. Refrigerant gases being powerful greenhouse gases, the challenge is to quickly detect leaks with the best possible sensitivity. The execution constraints were:

  • real-time analysis
  • a large volume of data
  • the reliability of the model

Our intervention

  • Data preparation: sampling, extraction
  • Data processing: various approaches tested (Machine Learning and Modeling)

Result & added value

  • Analysis report providing recommendations to better detect refrigerant loss

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