Category: Internet of Things

As COVID-19 cases continue to surge, institutions are working tirelessly to ensure they are prepared. Contact tracing is a complex problem to solve, and CareBand’s SafeTrack is a solution. This post covers how to get started partnering with CareBand’s technology and building a solution using AWS that collects data from SafeTrack wearables and integrates that with AWS IoT. The solution will generate a report of all the individuals who have been exposed to a detected case of COVID-19.

Itron Idea Labs has been leveraging IoT devices for decades and using technology in innovative ways, but they faced two major problems in developing solutions for public sector organizations: project delays, and large up-front costs. To overcome these challenges, Itron teamed up with TensorIoT and created a new route to integration in the form of the Itron Manhattan SDK, which gives IoT device manufacturers the ability to integrate their devices into the Itron Idea Labs Cloud and AWS.

AWS IoT Core offers a managed cloud service to support trillions of messages from billions of devices, and route messages easily and securely to devices and other AWS services. Learn how to use an AWS CloudFormation template to build the Actility ThingPark X connector to AWS IoT as the first step to connect LoRaWAN-enabled endpoints to AWS IoT Core, and to make use of other cloud services available on AWS.

Edge computing is a new paradigm in which the resources of a small data center are placed at the edge of the internet, in close proximity to mobile devices, sensors, and end users. Learn about the Physical Distancing Video Analytics Solution (VAS) on campus private 4G/5G networks that was developed utilizing AWS edge services in partnership with Carnegie Mellon University’s Open Edge Computing Initiative, Megh Computing’s Video Analytics Solution, and Federated Wireless Private Network Connectivity as a Service.

You can manage agents in a multi-tenant SaaS environment using AWS IoT Core. Review a solution that offers a modular and secure approach to register and manage agents. It relies on AWS managed services to offload the heavy lifting of implementing and maintaining those mechanisms, and provides scalability, elasticity, and availability. Using AWS IoT Core for agent management provides various capabilities for managing, securing, and analyzing usage and sent data from the registered agents.

Learn how to integrate a customer’s LoRaWAN devices connected to The Things Stack’s LoRaWAN Network Server with the AWS IoT Core service running in their account. This integration enables you to unleash the functionality available in the AWS IoT portfolio of services (and overall AWS ecosystem) for implementing solutions. The Things Stack is maintained by The Things Industries (TTI) and provides an integrated chain of products and services for customers to start working on IoT.

The growth of AI in a wide range of applications demands more purpose-built processors to provide scalable levels of performance, flexibility, and efficiency. The LG AIoT board helps customers accelerate their computer vision and machine learning journey using AWS. Learn how to build a simple AI-enabled application with AWS IoT Greengrass that takes advantage of the hardware AI acceleration on the LG AIoT board. AWS IoT Greengrass extends AWS on your device and offers the cloud programming model and tools at the edge.

Many companies today are challenged to ensure the resiliency of their supply chain operations against the disruption of geopolitical events, climate-related disasters, public health crises, and more. Explore how Deloitte’s IoT-enabled blockchain solution for supply chain can help organizations create transparency and promote trust in their supply chain with a single source of truth for product quality and traceability.mThe solution is powered by AWS IoT and Amazon Managed Blockchain services.

Inference is an important stage of machine learning pipelines that deliver insights to end users from trained neural network models. These models are deployed to perform predictive tasks like image classification, object detection, and semantic segmentation. However, constraints can make implementing inference at scale on edge devices such as IoT controllers and gateways challenging. Learn how to train and convert a neural network model for image classification to an edge-optimized binary for Intel FPGA hardware.

Connected devices require a complex combination of hardware, operating systems, and software to connect to the cloud. To simplify this development for customers, AWS works with Independent Hardware Vendors (IHV) that can integrate AWS IoT services. In this post, we explore three qualified AWS IoT Edge Software offerings, and dive deep on how these IHVs solve business use cases while enabling customers to use these software frameworks to connect to AWS IoT services.