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Amazon Web Services (AWS) made several announcements concerning availability of Industrial IoT edge offerings.
Machine to Cloud Connectivity Framework v2.2
The AWS Solutions team recently updated Machine to Cloud Connectivity Framework, a solution that provides secure factory equipment connectivity to the AWS Cloud. This solution is a framework to send equipment telemetry data to your AWS account, allowing you to leverage AWS Services to conduct analysis on your equipment data instead of managing underlying infrastructure operations. The solution currently allows for robust data ingestion using either the OPC Data Access (OPC DA) protocol or the CC-Link Partner Association (CLPA) Seamless Messaging Protocol (SLMP). Support for OPC Unified Access (OPC UA) protocol will follow in the next release.
This update adds the ability to automatically create a Greengrass group and supporting resources if you do not already have a Greengrass group set up and supports easier configuration of your Greengrass edge device.
For the OPC DA connector only, the update now allows you to send telemetry data to Amazon Kinesis Data Streams, in addition to an AWS IoT Topic. And finally, if you do not already have a Kinesis data stream, the update can automatically create a Kinesis Data Streams data dream, Kinesis Data Firehose delivery stream, and S3 bucket to store your data.
Support for linear interpolation in AWS IoT SiteWise
AWS IoT SiteWise, a managed service to collect, store, organize and monitor data from industrial equipment at scale, and supports linear interpolation, enabling customers to estimate and retrieve the values of missing data points in their time series data.
If your time series data is missing values at certain points in time, you can estimate and retrieve the values of those missing data points using the linear interpolation API. The linear Interpolation API helps to retrieve uniformly sampled data even if you have missing values or gaps in your raw data. To use the linear interpolation API, simply provide the AWS IoT SiteWise asset property, the time range, and the sampling frequency for the data you want to retrieve. The API will then return data points that meet your specified query parameters.
Customers can use the interpolation API for a number of use cases including filling in values for missing data points, retrieving uniformly sampled data and joining with uniformly sampled data from other data sources, or to downsample data to improve performance of their dashboards and/or reduce their data retrieval costs. As an example use case, customers can use the interpolation API to retrieve hourly measurement data (such as temperature) for their equipment (such as a pump) over a given week and join it with hourly data from their other data sources (such as shift/schedule data from ERP) to perform custom analytics operations.
New AWS Solutions Consulting Offer - IoT Resource Monitoring Framework
IoT Resource Monitoring Framework is an AWS Solutions Consulting Offer delivered via a consulting engagement from Trek10, an AWS IoT Competency Partner. IoT Resource Monitoring Framework gives companies clear and constant visibility into their IoT device and backend operations from a single pane. Customers that request this consulting offer will participate in an engagement that delivers a discovery session, AWS infrastructure deployment, a dashboard with monitors and alerts, and an application design document.
IoT Resource Monitoring Framework is a production-quality solution for understanding the health and behavior of your IoT ecosystems end to end—from the field and from edge devices to the supporting backend infrastructure. It uses underlying AWS services such as Amazon CloudWatch, Amazon DynamoDB, AWS IoT Core, and AWS IoT Device Defender.