AWS iot-sitewise documentation change
Summary
Expanded documentation about AWS IoT SiteWise architecture, workflows, and use cases. Added detailed sections about asset modeling, data analysis methods (alarms/queries/predictions), visualization access controls, storage tiers, and industry-specific implementations.
Security assessment
The changes add documentation about configuring access controls using IAM Identity Center/IAM for visualization dashboards, which is a security feature. However, there's no evidence this addresses a specific security vulnerability - it appears to be standard security documentation rather than a response to an incident.
Diff
diff --git a/iot-sitewise/latest/userguide/what-is-sitewise.md b/iot-sitewise/latest/userguide/what-is-sitewise.md index 1f832ae26..b3549492b 100644 --- a//iot-sitewise/latest/userguide/what-is-sitewise.md +++ b//iot-sitewise/latest/userguide/what-is-sitewise.md @@ -4,0 +5,2 @@ +How AWS IoT SiteWise worksUse cases for AWS IoT SiteWise + @@ -19 +21 @@ The following diagram shows the basic architecture of AWS IoT SiteWise: - * [How AWS IoT SiteWise works](./how-sitewise-works.html) + * How AWS IoT SiteWise works @@ -21 +23 @@ The following diagram shows the basic architecture of AWS IoT SiteWise: - * [Use cases for AWS IoT SiteWise](./use-cases.html) + * Use cases for AWS IoT SiteWise @@ -29,0 +32,96 @@ The following diagram shows the basic architecture of 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](https://console.aws.amazon.com/iotsitewise/). You can also configure asset models to collect and process data at the edge or in the AWS Cloud. + +###### Topics + + * [Ingest industrial data](./how-it-works-ingest-data.html) + + * Model assets to contextualize gathered data + + * Analyze using queries, alarms, and predictions + + * Visualize operations + + * Store data + + * Integrate with other services + + + + +### 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 [Model industrial assets](./industrial-asset-models.html). + +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](./integrate-tm.html#it-integrate). + +### 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 [Monitor data with alarms in AWS IoT SiteWise](./industrial-alarms.html). + + * 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](./query-industrial-data.html). + + * 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 [Detect anomalies with Lookout for Equipment](./anomaly-detection.html). + + + + +### 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](https://docs.aws.amazon.com/iot-sitewise/latest/appguide/) for these employees to learn how to use SiteWise Monitor. + +For more information on visualizing your operations, see [Monitor data with AWS IoT SiteWise Monitor](./monitor-data.html). + +### 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 [Manage data storage in AWS IoT SiteWise](./manage-data-storage.html). + +You can also import and export asset metadata. For more information see [Asset metadata](./file-path-and-schema.html#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 [Interact with other AWS services](./interact-with-other-services.html). + +## Use cases for AWS IoT SiteWise + +AWS IoT SiteWise is used across a variety of industries for many industrial data collection and analysis applications. + +Collect data consistently from all your sources to help resolve issues quickly. AWS IoT SiteWise offers remote monitoring to collect the data directly on-site or gather it from multiple sources across many facilities. AWS IoT SiteWise provides the necessary flexibility for industrial IoT data solutions. + +### Manufacturing + +AWS IoT SiteWise can simplify the process of collecting and utilizing data from your equipment to pinpoint and minimize inefficiencies, enhancing industrial operations. AWS IoT SiteWise helps you collect data from manufacturing lines and equipment. With AWS IoT SiteWise, you can transfer the data to the AWS Cloud and build performance metrics for your specific equipment and processes. You can use the metrics produced to understand the overall effectiveness of your operations and identify opportunities for innovation and improvement. You can also view your manufacturing process and identify equipment and process deficiencies, production gaps, or product defects. + +### Food and beverage + +Food and beverage industry facilities handle a wide variety of food processing, including grinding grain to flour, butchering and packing meat, and assembling, cooking, and freezing microwaveable meals. Food processing plants often span multiple locations with plant and equipment operators in a centralized location to monitor processes and equipment. For example, refrigeration units assess ingredient handling and expiration. They monitor waste creation across facilities to ensure operational efficiency. With AWS IoT SiteWise, you can group sensor data streams from multiple locations by production line, and facilities so your process engineers can better understand and make improvements across facilities. + +### Energy and utilities + +With AWS IoT SiteWise, you can resolve equipment issues easier and more efficiently. You can monitor asset performance remotely and in real time. Access historical equipment data from anywhere to pinpoint potential problems, dispatch accurate resources, and both prevent and fix issues faster. + @@ -36 +134 @@ To use the Amazon Web Services Documentation, Javascript must be enabled. Please -How AWS IoT SiteWise works +Working with AWS SDKs