The Internet of Things on AWS – Official Blog
Category: Learning Levels
Optimize image classification on AWS IoT Greengrass using ONNX Runtime
Introduction Performing machine learning inference on edge devices using models trained in the cloud has become a popular use case in Internet of Things (IoT) as it brings the benefits of low latency, scalability, and cost savings. When deploying models to edge devices with limited compute and memory, developers have the challenge to manually tune […]
How to build smart applications using Protocol Buffers with AWS IoT Core
Introduction to Protocol Buffers Protocol Buffers, or Protobuf, provide a platform-neutral approach for serializing structured data. Protobuf is similar to JSON, except it is smaller, faster, and is capable of automatically generating bindings in your preferred programming language. AWS IoT Core is a managed service that lets you connect billions of IoT devices and route […]
How to get started with the new AWS IoT Core Device Location service
Introduction The new AWS IoT Core Device Location feature allows Internet of Things (IoT) devices to retrieve and report their current location without relying on Global Positioning System (GPS) hardware. Devices and clients connected to AWS IoT Core can now use cloud-assisted Global Navigation Satellite System(GNSS), WiFi scan, cellular triangulation, and reverse IP lookup techniques […]
How to reduce latency with Amazon Kinesis Video Streams – Part 2
In this, part 2 on how to reduce latency in media managed by Amazon Kinesis Video Streams (KVS) I describe the techniques in which to configure KVS, the media producer and the media player for optimal latency settings. Then, I introduce the Amazon Kinesis Video Stream Web Viewer and perform a number of experiments on […]
How to reduce latency with Amazon Kinesis Video Streams – Part 1
In this two part series I describe how to reduce latency of streaming media managed by Amazon Kinesis Video Streams and how less than 2-second latency can be delivered with robust video quality across a variety of network conditions. Then, I provide a practical demonstration showing that with the Amazon Kinesis Video Stream Web Viewer, […]
Introducing new MQTTv5 features for AWS IoT Core to help build flexible architecture patterns
Introduction We are excited to announce that AWS IoT Core now supports MQTTv5 features that help enhance communications of large-scale device deployments and innovate device messaging patterns. Customers who already have MQTTv3.1.1 deployments can make use of the new MQTTv5 features as AWS IoT Core provides seamless integration between both versions and supports heterogeneous deployments […]
Reduce building maintenance costs with AWS IoT TwinMaker Knowledge Graph
Introduction The shift from in office work to hybrid and fully remote work is causing revenue and valuation pressure on commercial building owners. As a result, building managers are exploring ways to optimize their expenses by reducing maintenance costs while still providing a premier tenant experience. Building managers are responsible for maintenance and providing a […]
Importing AWS IoT Device Defender audit and detect findings into Security Hub
Introduction In this post, you’ll learn how the integration of IoT security findings into AWS Security Hub works, and you can download AWS CloudFormation templates to implement the solution. After you deploy the solution, every AWS IoT Device Defender audit and detect finding will be recorded as a Security Hub finding. The findings within Security […]
Integrating AWS IoT SiteWise and Fleet Hub with IAM Identity Center and Okta
Introduction Many organizations are using an external identity provider to manage user identities. With an identity provider (IdP), you can manage your user identities outside of AWS and give these external user identities permissions to use AWS resources in your AWS accounts. External identity providers (IdP), such as Okta Universal Directory, can integrate with AWS […]
Developing a Remote Job Monitoring Application at the edge using AWS IoT Greengrass (part 1)
Introduction Many modern industrial operations require extensive monitoring and real-time decision making for efficiency and safety reasons. To reduce the unexpected network interruption and delay in IoT data processing, edge computing becomes a desirable option for real-time IoT data processing and monitoring. Edge computing is a system of micro computing/storage devices that are installed at […]