The Internet of Things on AWS – Official Blog

Category: SageMaker

AWS IoT named Best Consumer IoT Solution at 2020 IoT World Awards

AWS IoT Named “Best Consumer IoT Solution” at 2020 IoT World Awards

At AWS, we build technology to help customers and partners like Bose, Vizio, LG, British Gas Centrica Connected Home, Ayla, NXP, and more solve real world problems and unlock possibilities to create better business outcomes and new consumer experiences. Yesterday, IoT World named AWS IoT the “Best Consumer IoT Solution” for 2020. We are grateful to […]

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Training the Amazon SageMaker object detection model and running it on AWS IoT Greengrass – Part 3 of 3: Deploying to the edge

Training the Amazon SageMaker object detection model and running it on AWS IoT Greengrass – Part 3 of 3: Deploying to the edge

Post by Angela Wang and Tanner McRae, Senior Engineers on the AWS Solutions Architecture R&D and Innovation team This post is the third in a series on how to build and deploy a custom object detection model to the edge using Amazon SageMaker and AWS IoT Greengrass. In the previous 2 parts of the series, we walked […]

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Training the Amazon SageMaker object detection model and running it on AWS IoT Greengrass – Part 2 of 3: Training a custom object detection model

Training the Amazon SageMaker object detection model and running it on AWS IoT Greengrass – Part 2 of 3: Training a custom object detection model

Post by Angela Wang and Tanner McRae, Engineers on the AWS Solutions Architecture R&D and Innovation team This post is the second in a series on how to build and deploy a custom object detection model to the edge using Amazon SageMaker and AWS IoT Greengrass. In part 1 of this series, we walked through the training […]

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Training the Amazon SageMaker object detection model and running it on AWS IoT Greengrass – Part 1 of 3: Preparing training data

Training the Amazon SageMaker object detection model and running it on AWS IoT Greengrass – Part 1 of 3: Preparing training data

Post by Angela Wang and Tanner McRae, Engineers on the AWS Solutions Architecture R&D and Innovation team Running computer vision algorithms at the edge unlocks many industry use cases that has low or limited internet connectivity. Combining services from AWS in the Machine Learning (ML) and Internet of Things (IoT) space, training a custom computer vision model and running […]

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Improving industrial safety with video analytics, AWS IoT Core, and AWS IoT Greengrass

Improving industrial safety with video analytics, AWS IoT Core, and AWS IoT Greengrass

Industrial customers are increasingly using the AWS Cloud to meet their targets for predictive quality, predictive maintenance, and asset condition monitoring. For more examples, see the Top Use Cases for Industrial IoT Applications ebook. The first of these, predictive quality, is often strongly correlated with the level of safety in an operating environment. In this […]

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Machine Learning at the Edge: Using and Retraining Image Classification Models with AWS IoT Greengrass (Part 2)

In part 1 of this blog post, we created an image classification model for a recycling facility’s sorter to identify four beverage containers. We deployed it to our AWS IoT Greengrass Core device using the new AWS IoT Greengrass Image Classification connector. AWS IoT Greengrass connectors, announced at this year’s re:Invent, make it possible for […]

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Machine Learning at the Edge: Using and Retraining Image Classification Models with AWS IoT Greengrass (Part 1)

With the introduction of the AWS IoT Greengrass Image Classification connector at this year’s re:Invent, it has become easier than ever to use image classification at the edge through AWS IoT Greengrass. Because it is software that lives on a local device, AWS IoT Greengrass makes it possible to analyze data closer to the source […]

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Using AWS IoT for Predictive Maintenance

The interest in machine learning for industrial and manufacturing use cases on the edge is growing. Manufacturers need to know when a machine is about to fail so they can better plan for maintenance. For example, as a manufacturer, you might have a machine that is sensitive to various temperature, velocity, or pressure changes. When […]

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Using Chainer Neural Network Framework with AWS Greengrass ML Inference

Starting today, Greengrass ML inference includes a pre-built Chainer package for all devices powered by Intel Atom, NVIDIA Jetson TX2, and Raspberry Pi. So, you don’t have to build and configure the ML framework for your devices from scratch. With this launch, we now provide pre-built packages for three popular machine learning frameworks including TensorFlow, […]

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