Revolutionizing Asset Modeling with AWS IoT SiteWise
Industrial and manufacturing customers are increasingly turning to AWS IoT SiteWise for their data collection, storage, organization, and monitoring needs. AWS IoT SiteWise serves as a robust industrial data foundation, supporting remote equipment monitoring, performance tracking, anomaly detection, and advanced analytics.
Efficiently building this data foundation involves asset modeling and ingesting telemetry data, which can be a complex process when dealing with a large number of equipment and dynamic operations seeking operational efficiency.
At re:Invent 2023, AWS introduced three new features to enhance asset modeling efforts on AWS IoT SiteWise. These features include Asset Model Components for component representation, Metadata Bulk Operations for bulk modeling, and User-defined Unique Identifiers for organizational consistency.
In this blog post, we will delve into real-world customer scenarios related to asset modeling and provide code examples to showcase the new AWS IoT SiteWise features.
Prerequisites
- Familiarity with asset modeling in AWS IoT SiteWise
- An AWS account
- Basic knowledge of Python
Setting Up Your Environment
To begin, configure your developer workstation with AWS credentials and ensure Python is installed. Install Git, clone a code example project, and create an IAM policy for bulk operations.
- Create a Cloud9 environment or use an on-premises workstation
- Configure AWS credentials
- Verify Python 3.x installation
- Install Git and clone the Metadata Bulk Operations Sample repository
- Install required Python packages
- Update project configuration details
- Create an IAM policy for bulk operations
Scaling Asset Management with Bulk Operations
AWS IoT SiteWise now supports bulk import, export, and update of industrial equipment metadata, enabling users to scale asset management efficiently. New API endpoints facilitate these bulk operations, providing a seamless process for onboarding and updating assets and asset models.
Metadata bulk import jobs play a crucial role in asset modeling, streamlining the process through a defined workflow as depicted in the diagram provided.
Real-World Scenarios for Asset Modeling
Scenario 1 – Onboard Initial Asset Models & Assets
Start by onboarding a subset of equipment to AWS IoT SiteWise, importing asset models and assets in bulk to kick off your asset modeling journey.
Scenario 2 – Define Asset Hierarchy
Establish asset hierarchies to track performance across different organizational levels, providing a comprehensive view of equipment relationships.
Maintaining Consistency and Reusability
AWS IoT SiteWise enables users to maintain consistency across their organization through user-defined unique identifiers and asset model components, ensuring standardization and reusability.
Scenario 10 – Apply External Identifiers
Implement external IDs to map existing identifiers with AWS IoT SiteWise UUIDs, promoting standardized asset management practices.
Enhancing Asset Modeling with Component Models
Introducing component models on AWS IoT SiteWise allows for standardized equipment modeling and reusability, fostering efficient asset management practices.
Scenario 11 – Compose Asset Models
Compose asset models by grouping components to create a holistic representation of equipment, facilitating a comprehensive view of assets.
Conclusion
The new features on AWS IoT SiteWise revolutionize asset modeling practices, offering enhanced scalability, standardization, and consistency in industrial asset management. By leveraging these capabilities, organizations can streamline their asset modeling initiatives and drive operational efficiency.
About the Authors
Meet Author Name, a Senior WorldWide IIoT Specialist Solutions Architect at AWS, with a wealth of experience in empowering industrial manufacturers with IoT data insights.