QuestionQ42

Analyzing and optimizing technical and business processes

Operational settings, such as oil pressure, can be adjusted on each of TerramEarth's vehicles to improve efficiency according to environmental conditions. Your primary objective is to improve the operating efficiency of all 20 million cellular and unconnected vehicles in the field.

How can you achieve this objective?

  • A Have you engineers inspect the data for patterns, and then create an algorithm with rules that make operational adjustments automatically
  • B Capture all operating data, train machine learning models that identify ideal operations, and run locally to make operational adjustments automatically
  • C Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically
  • D Capture all operating data, train machine learning models that identify ideal operations, and host in Google Cloud Machine Learning (ML) Platform to make operational adjustments automatically
Explanation

Models trained on operating data can learn the relationship between environmental conditions and efficient vehicle settings. Running inference locally enables automatic adjustments with low latency and continues to function when a vehicle has no network connection; cloud-hosted inference or cloud messaging cannot reliably serve unconnected vehicles.

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