The Internet of Things on AWS – Official Blog

Category: Best Practices

AWS IoT for Industrial Solutions

Industrial IoT – From Condition Based Monitoring to Predictive Quality to digitize your factory with AWS IoT Services

Industrial IoT (IIoT) bridges the gap between industrial equipment and automation networks (usually called OT, Operations Technology) and Information Technology (IT). In IT, use of new technologies such as machine learning, cloud, mobile, and edge computing are becoming commonplace. IIoT brings machines, cloud computing, analytics, and people together to improve performance, productivity, and efficiency of […]

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Improving the management and security of your AWS IoT resources with tagging

Improving the management and security of your AWS IoT resources with tagging

Solution providers operating environments such as smart building, utilities, manufacturing systems, and connected products offer business-to-business services often based on IoT platforms deployed in multitenant deployments. Securely managing those resources by use case, types, locations and by tenants can sometime be hard. Creating hierarchical grouping of things is a common pattern, but it does not […]

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Collecting, organizing, monitoring, and analyzing industrial data at scale using AWS IoT SiteWise

Collecting, organizing, monitoring, and analyzing industrial data at scale using AWS IoT SiteWise (Part 2)

Post by Asim Kumar Sasmal, Senior Data Architect in the IoT Global Specialty Practice of AWS Professional Services and Sourav Chakraborty, Senior Product Manager of AWS IoT SiteWise.   [Before reading this post, read Part 1 in the series.] In Part 1 of this series, you learned how to model and ingest data from industrial sites in a […]

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AWS IoT SiteWise Overview

Collecting, organizing, monitoring, and analyzing industrial data at scale using AWS IoT SiteWise (Part 1)

Post by Saras Kaul, Senior Product Manager of IoT SiteWise, Asim Kumar Sasmal, Senior Data Architect, and Mark Gilbert, Senior Consultant in the IoT Global Specialty Practice of AWS Professional Services.   Industrial customers have been looking for a secure, cost-effective, and reliable field-to-cloud solution that does the following: Ingests all their data from hundreds of industrial sites that […]

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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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Chain of trust in a device starting from Applications and flowing down through Operating System, Hypervisor, Firmware and finally ending at the Hardware which forms the root of trust.

Using a Trusted Platform Module for endpoint device security in AWS IoT Greengrass

Co-authored by Aniruddh Chitre, AWS Solutions Architect This post demonstrates how AWS IoT Greengrass can be integrated with a Trusted Platform Module (TPM) to provide hardware-based endpoint device security. This integration ensures the private key used to establish device identity can be securely stored in tamper-proof hardware devices to prevent it from being taken out […]

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Support for Secure Elements in FreeRTOS

Secure elements represent a category of devices intended to enhance security in connected devices. For microcontroller (MCU)–based devices, secure elements provide tamper-resistant storage of private keys and certificates, and offloading of cryptographic functions from the host microcontroller. You can now leverage two new qualifications that include support for secure elements within Amazon FreeRTOS.  These qualifications […]

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Securing Amazon FreeRTOS devices at scale with Infineon OPTIGA Trust X

Post by David Walters, Senior Partner Specialist Solutions Architect, IoT at Amazon Web Services, and Artem Yushev, Applications Engineer, Embedded Security Systems, at Infineon. One of the most significant challenges for device manufacturers developing new microcontroller-based IoT devices is how to manufacture and provision those devices at scale without compromising security. In this blog post, we […]

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