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Crosser Low Code Data Flow - Condition Monitoring IIoT

In this example, the flow is reading OPC-DA data and prepare it for a Python model running at the edge:

  1. Apply algorithms to extract features from the data, eg objects, patterns, trends…
  2. Correlate data from multiple sensors to derive higher-level insights
  3. Use compression techniques to reduce the amount of data without reducing the relevant information.

Steps

  1. Collect OPC data
  2. Pre-process data
  3. Time align
  4. Run Machine Learning model

Introduction to Machine Learning at the Edge

Free on-demand webinar

Intro to applying Machine Learning at the Edge. During this 30 min session, Crosser CTO, Goran Appelquist Ph.D. will introduce you to designing a functional IOT data flow for industrial usage within Crosser Flow Studio.

Level: Intermediate
Time: 00:30:31

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Sign up for a free trial account. Design and deploy your first Flows today.

  1. Sign up
  2. Login and start designing your data flows
  3. Run the flow in Crosser test environment or download local test node
  4. Test with real data

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