Wind Turbine Anomaly Detection sample application demonstrates a time series use case by detecting the anomalous power generation patterns relative to wind speed. By identifying deviations, it helps optimize maintenance schedules and prevent potential turbine failures, enhancing operational efficiency.
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Overview
- Overview: A high-level introduction.
- Architecture: High Level Architecture.
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Getting Started
- System Requirements: Hardware and software requirements for running the sample application.
- Get Started: Step-by-step guide to getting started with the docker compose deployment of the sample application.
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Deployment
- How to Deploy with Helm: Guide for deploying the sample application on a k8s cluster using Helm.
- How to Deploy with Edge Orchestrator: Guide for deploying the sample application using Edge Manageability Framework
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Advanced
- How to build from source and deploy: Guide to build from source and docker compose deployment
- How to configure OPC-UA/MQTT alerts: Guide for configuring the OPC-UA/MQTT alerts in the Time Series Analytics microservice
- How to configure custom UDF deployment package: Guide for deploying a customized UDF deployment package (udfs/models/tick scripts)
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Release Notes
- Release Notes: Information on the latest updates, improvements, and bug fixes.