The Internet of Things on AWS – Official Blog

Tag: Edge devices

AWS IoT Greengrass now supports the Windows operating system

Introduction Microsoft Windows is a common operating system for devices used in industrial automation. Customers using AWS IoT Greengrass have been restricted to Linux based devices until now. Today we are excited to announce native Windows support for AWS IoT Greengrass v2. This will allow customers to leverage AWS IoT Greengrass on their Windows based […]

Read More
The following diagram presents the architecture of the solution demonstrated in this post.

How to integrate NVIDIA DeepStream on Jetson Modules with AWS IoT Core and AWS IoT Greengrass

AWS continually evolves our edge computing offerings to provide customers with the technology they need to extend AWS services to edge devices, such as consumer products or manufacturing equipment, and enable them to act intelligently. This helps customers avoid unnecessary cost and latency, and empower customers with the ability to manage edge devices securely and […]

Read More
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 […]

Read More
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 […]

Read More