Isolation Forest Anomaly Detection Model

Isolation Forest Anomaly Detection Model

credit(s)

Maximo Asset Monitor

The Isolation Forest Anomaly Detection Model for  IBM® Maximo® Asset Monitor  applies the open source model and includes specialized IoT models,  analysis notebooks, functions, and dashboards for Anomaly Detection.


Download limit: unlimited
Download availability: 365 days
Add to Wishlist

Description

This Digital Twin provides a  Custom Function  to retrieve  data from Maximo asset Monitor and invoke  an external  Model service running Isolation Forest Python Model. Once the data is analyzed by the service, the score can then be persisted in the Monitor database for predicting asset behaviour and models
The use case here is to detect anomalies within a Maximo Asset Monitor dataset using a scikit-learn model, which is externally hosted in a Watson Machine Learning service. Anomalies are able to be visualized and metric  correlations between anomalies via time-series graphs.
When the data scientist  has trained and tested this model with their asset , they will understand how to:
  • Load asset data into Monitor
  • Forward data to external services via REST HTTP call.
  • Build a dashboard using Maximo Asset Monitor to monitor, visualize, and analyze IOT asset data and Anomalies
  • Generate alerts when certain results are received.
The intended audience for this Model  are developers / data scientists who would like to analyze their data  Monitor via customized machine learning models that are hosted externally.

Additional information

Industry

Oil & Gas

Digital Twin Resources

, ,

Reviews

There are no reviews yet.

Only logged in customers who have purchased this product may leave a review.

Refund Policy

- not applicable -

Cancellation / Return / Exchange Policy

Product is offered as a free, non-supported example of an open source model packaged for Maximo Asset Monitor.  Please submit any questions as a direct message to AI Applications Store, or use site resources for help.

End User License Agreement

General Inquiries

There are no inquiries yet.

Related Digital Twins