Category: Best Practices

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 […]

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 […]

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 […]

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 […]

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 […]

Gaining access to sensor data or telemetry of industrial machines is a key requirement for implementing high-value use cases around smart manufacturing or Industry 4.0. For instance, predictive maintenance or automated quality control is not possible without having such data at a high temporal resolution. Given the heterogeneous environment of modern industrial production lines with […]

For many people, getting a package delivered from Amazon is painless. However, problems can arise in access-controlled properties such as apartment complexes, condominiums, and businesses. This post tells how an Amazon team developed Amazon Key for Business to address this issue. Overview Amazon strives to make its package delivery process quick and easy for customers. […]

AWS IoT Greengrass extends AWS managed services to edge device systems, providing security, message routing, and local state processing. It also provides a central hub for connectivity with other AWS services using AWS Lambda functions. Some edge systems with multiple devices produce high-frequency updates, such as device shadow updates. It can be difficult to determine […]

The AWS IoT Analytics platform offers configurable dataflows for processing messages from IoT devices, which can be either uni-schema or multi-schema. When you have billions of messages and millions of IoT devices, you need efficient designs for message-processing dataflows. In this post, you do a deep dive into various aspects of designing dataflows. You learn […]

Hardware and operating systems for edge devices are built and delivered to customers in a wide range of form factors, such as consumer gateways, industrial controllers, and in-vehicle infotainment systems. Original design manufacturers (ODMs) and original equipment manufacturers (OEMs) building commercial off-the-shelf products decide which hardware and software combinations to use. System integrators (SIs) developing […]