Integrating Azure Anomaly Detection with my IoT system (on prime)

Mohamed Wahba 0 Reputation points

I have an IoT system which is deployed on our Prime ( Local Servers) , and we can collect real-time data from PLCs' and show this data in dashboards and make reports . I would like to apply Azure Anomaly detection module to this comprehensive data and train models to detect problems , and next step to have predictive maintenance system . How can I start ?

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  1. YutongTie-MSFT 45,911 Reputation points

    Hello Mohamed Wahba

    Thanks for reaching out to us. I think you want to use the data from your IoT system as the input to Azure Anomaly Detector. I hope below content can help you start smoothly.

    I will first invite you to try on the interactive demo to know which kind of model you need -

    There are two kind of detectors - Univariate Anomaly Detector and Multivariate Anomaly Detector

    Multivariate Anomaly Detector

    This demo shows you how Multivariate Anomaly Detector detects anomalies from time series data among multiple variables automatically.

    User's image

    You can use Anomaly Detector multivariate for -

    • Detect system level anomalies from a group of time series.
    • When any individual time series won't tell you much and you have to look at all signals to detect a problem.
    • Predicative maintenance of expensive physical assets with tens to hundreds of different types of sensors measuring various aspects of system health.

    Univariate Anomaly Detector

    This demo shows you how Anomaly Detector detects anomalies from time series data automatically in streaming or batch ways. Anomaly Detector learns from the time series data in the API requests about the normal pattern and generates output on which data points are anomalies, expected values, upper/lower bounds. You can also see how the sensitivity parameter can impact detection results and upper/lower bounds of normal value range dynamically, the higher the value, the narrower the band and the more anomalies would be marked.

    The demo provides three samples for you to have a try

    User's image

    Use the Anomaly Detector for

    • Detect anomalies throughout your time series data set, as a batch request
    • Detect the anomaly status of the latest data point in your time series
    • Detect trend change points in your data set.

    When you decide which detector to use, you can refer to the below repo for the code of the demo

    Quickstart: Use the Univariate Anomaly Detector client library

    Quickstart: Use the Multivariate Anomaly Detector client library

    You can choose your preference language to develop. I hope this helps, please let me know if you need further help.



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