How AWS IoT SiteWise works - AWS IoT SiteWise

How AWS IoT SiteWise works

AWS IoT SiteWise offers a resource modeling framework that you can use to create representations of your industrial devices, processes, and facilities. The representations of your equipment and processes are called asset models in AWS IoT SiteWise. With asset models, you define the raw data to consume and how to process it into useful metrics. Build and visualize assets and models for your industrial operation in the AWS IoT SiteWise console. You can also configure asset models to collect and process data at the edge or in the AWS Cloud.

Ingest industrial data

Begin to use AWS IoT SiteWise by ingesting industrial data. Ingesting your data is done in one of several ways:

  • Direct ingestion from on-site servers: Utilize protocols like OPC-UA to read data directly from on-site devices. Deploy the SiteWise Edge gateway software, compatible with AWS IoT Greengrass V2, on a wide range of platforms such as common industrial gateways or virtual servers. You can connect up to 100 OPC-UA servers to a single AWS IoT SiteWise gateway. For more information, see SiteWise Edge gateway requirements.

    Note that protocols like Modbus TCP and Ethernet/IP (EIP) are supported through our partnership with Domatica in the context of AWS IoT Greengrass V2.

  • Edge data processing with packs: Enhance your SiteWise Edge gateway by adding packs to enable comprehensive edge capabilities. With SiteWise Edge, available on AWS IoT Greengrass V2, data processing is executed directly on-site before being securely transmitted to the AWS Cloud using an AWS IoT Greengrass stream. For more information, see Using packs.

  • Adaptive ingestion via Amazon S3 with bulk operations: When working with large numbers of assets or asset models, use bulk operations to bulk import and export resources from Amazon S3 buckets. For more information, see Bulk operations with assets and models.

  • MQTT messages with AWS IoT Core Rules: For devices connected to AWS IoT Core sending MQTT messages, employ the AWS IoT Core rules engine to direct those messages to AWS IoT SiteWise.If you have devices connected to AWS IoT Core sending MQTT messages, use the AWS IoT Core rules engine to route those messages to AWS IoT SiteWise. For more information, see Ingesting data using AWS IoT Core rules.

  • Event-triggered data ingestion: Use AWS IoT Events actions to configure the IoT SiteWise action in AWS IoT Events to send data to AWS IoT SiteWise when events occur. For more information, see Ingesting data from AWS IoT Events.

  • AWS IoT SiteWise API: Your applications at the Edge or in the cloud can directly send data to AWS IoT SiteWise. For more information, see Ingesting data using the AWS IoT SiteWise API.

Model assets to contextualize gathered data

After ingesting data, you can use the data to create virtual representations of your assets, processes, and facilities by building models of your physical operations. An asset, representing a device or process, transmits data streams to the AWS Cloud. Assets can also signify logical device groupings. Hierarchies are formed by associating assets to mirror complex operations. These hierarchies allow assets to access data from associated child assets. Assets are created from asset models. Asset models are declarative structures that standardize asset formats. Reuse components of assets for organization and maintainability of your models. For more information, see Modeling industrial assets.

With AWS IoT SiteWise, you can configure your assets to transform the incoming data into contextual metrics and transforms.

  • Transforms work when receiving equipment data.

  • Metrics are calculated at intervals you define.

Metrics and transforms are applicable to both individual assets or multiple assets.AWS IoT SiteWise automatically computes commonly used statistical aggregates like average, sum, and count, across various time frames relevant to your equipment data, metrics, and transforms.

Assets can be synchronized using AWS IoT TwinMaker. For more information, see Integrating AWS IoT SiteWise and AWS IoT TwinMaker.

Analyze using queries, alarms, and predictions

Analyze the date gathered with AWS IoT SiteWise by running queries and setting up alarms. You can also use Amazon Lookout to automatically detect anomalies within metrics and identify their root causes.

  • Set specific alarms to alert your team when equipment or processes deviate from optimal performance, ensuring quick issue identification and resolution. For more information, see Monitoring data with alarms.

  • Use the AWS IoT SiteWise API operations to query your asset properties' current values, historical values, and aggregates over specific time intervals. For more information, see Query data from AWS IoT SiteWise.

  • Use anomaly detection with Amazon Lookout for Equipment to identify and visualize changes in equipment or operating conditions. With anomaly detection, you can determine preventative maintenance measures for your operations. This integration allows customers to sync data between AWS IoT SiteWise and Amazon Lookout for Equipment. For more information, see Detecting equipment anomalies with Amazon Lookout for Equipment.

Visualize operations

Set up SiteWise Monitor to create web applications for your operational employees. The web applications help employees to visualize your operations. Handle varied levels of access for your employees using IAM Identity Center or IAM. Configure unique logins and permissions for each employee to view specific subsets of an entire industrial operation. AWS IoT SiteWise provides an application guide for these employees to learn how to use SiteWise Monitor.

For more information on visualizing your operations, see Monitoring data with AWS IoT SiteWise Monitor.

Store data

You can integrate time series storage with your industrial data lake. AWS IoT SiteWise has three storage tiers for industrial data:

  • A hot storage tier that is optimized for real-time applications.

  • A warm storage tier optimized for analytical workloads.

  • A customer-managed cold storage tier using Amazon S3 for operational data applications with high latency tolerance.

AWS IoT SiteWise helps you manage storage cost by keeping recent data in the hot storage tier. Then, you define data retention policies to move historical data to warm or cold tier storage. For more information, see Managing data storage.

You can also import and export asset metadata. For more information see Asset metadata.

Integrate with other services

AWS IoT SiteWise integrates with several AWS services to develop a complete AWS IoT solution in the AWS Cloud. For more information, see Interacting with other AWS services.