Overview
Saving telemetry to ThingsBoard allows you to persist anomaly detection results such as anomaly scores and score indexes as time series data.
This enables further analysis, visualization, and alerting within ThingsBoard.
Configuration
To save telemetry data to ThingsBoard, follow these steps in your anomaly detection model configuration:
1. Configure Telemetry Key and Storage Frequency
- Telemetry Key: Specify the telemetry key under which anomaly scores and score indexes will be saved in ThingsBoard.
- Telemetry Storage Frequency: Define how frequently telemetry data should be stored.
It is recommended to set this frequency lower than:- the segment time range (for fixed segments), or
- the product of segment size and sliding step (for sliding windows).
This helps prevent overlapping anomalies.
Note: It is not recommended to set the telemetry storage frequency lower than 1 hour, as this can cause performance pressure on ThingsBoard.
Warning: Changing the telemetry storage frequency after running the first refresh may lead to inconsistent or overlapping data in ThingsBoard. It is recommended to finalize the frequency setting before enabling telemetry saving.
2. Enable Anomaly Refresh
To activate telemetry saving, anomaly refresh must be enabled with the “Enable Saving Anomaly Data” toggle.
Read more about enabling refresh here.
Once refresh is enabled, the required entity fields in Trendz will be created automatically.
If refresh is later disabled, telemetry saving will also stop automatically and the required entity fields will be disabled.
The telemetry data already stored will remain in ThingsBoard, even if the model is deleted.
Telemetry data can be saved during both Refresh and Reprocess, provided that the “Enable Saving Anomaly Data” flag is enabled in the refresh settings.
Next Steps
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Getting started guide - These guide provide quick overview of main Trendz features.
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Installation guides - Learn how to setup ThingsBoard on various available operating systems.
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Calculated Fields - Learn about Calculated fields and how to use them.
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States - Learn how to define and analyse states for assets based on raw telemetry.
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Prediction - Learn how to make forecasts and predict telemetry behavior.
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Filters - Learn how filter dataset during analysis.
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Available Visualizations - Learn about visualization widgets available in Trendz and how to configure them.
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Share and embed Visualizations - Learn how to add Trendz visualizations on ThingsBoard dashboard or 3rd party web pages.
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AI Assistant - Learn how to utilize Trendz AI capabilities.