AWS to talk IoT at AWS Summit Sydney


“We understand that for many IoT use cases, IoT data needs to be collected, processed and actioned at the edge – where the customer’s business runs,” he told IoT Hub.
“To reflect that, we will be showcasing the capabilities of AWS Greengrass in delivering IoT edge intelligence with integration to other services such as Amazon Rekognition and AWS Machine Learning solutions.”

AWS Greengrass, Hickin explained, is software to run local compute, messaging, data caching, sync, and machine learning inference capabilities for connected devices in a secure way.

“With AWS Greengrass, connected devices can run AWS Lambda functions, keep device data in sync, and communicate with other devices securely – even when not connected to the Internet,” he said.

“Using AWS Lambda, AWS Greengrass ensures your IoT devices can respond quickly to local events, use Lambda functions running on AWS Greengrass Core to interact with local resources, operate with intermittent connections, stay updated with over the air updates, and minimise the cost of transmitting IoT data to the cloud.”

A new feature, AWS Greengrass ML Inference, brings machine learning services to the edge. “It lets application developers add machine learning models to their devices and edge hardware so that complex machine learned models (prediction, classification etc) can be run and executed on the edge – close to the data,” Hickin said.


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