This open-source solution template showcases a complete Azure infrastructure capable of supporting Predictive Maintenance scenarios in the context of IoT remote monitoring. This repo provides reusable and customizable building blocks to enable Azure customers to solve Predictive Maintenance problems using Azure's cloud AI services.

• Automated deployment to Azure
• Sample Jupyter notebooks covering feature engineering, model training, evaluation and operationalization
• Configurable and extensible data generator (supports static and streaming modes)
• Technical documentation
• Demo dashboard featuring IoT device management, live metrics, and prediction visualization
• Integration with Linux Data Science Virtual Machine (DSVM) and Azure Databricks
• Compliance with Team Data Science Process (TDSP)

You will need an Azure subscription to get started.

Deploying the solution will create a resource group in your subscription and populate it with the following resources:

• Azure Storage account
• Azure App Service
• Data Science Virtual Machine (DSVM)
• Azure Databricks workspace and cluster
• Azure IoT Hub
• Azure Container Instances (ACI) application

If you discover any bugs, please file an issue here, making sure to fill out the provided template with the appropriate information.

To share your feedback, ideas or feature requests, please contact [email protected].

• Documentation
• Azure AI guide for predictive maintenance solutions

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.