AWS Partner Network (APN) Blog

Tag: Internet of Things

Healthcare-2

How to Build and Deploy a Contact Tracing Solution with AWS IoT Core and SafeTrack Lite

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.

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1NCE-AWS-Partners

Automated Device Provisioning to AWS IoT Core Using 1NCE Global SIM

AWS IoT Core offers a managed cloud services to ingest trillions of messages from billions of devices, and easily and securely interact with other AWS cloud services and other devices. Learn how you can use the 1NCE IoT Connectivity Suite to take the complexity out of IoT projects and overcome the challenges of cellular IoT adoption. 1NCE is an AWS Advanced Technology Partner that offers managed connectivity services for low bandwidth IoT applications.

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How TensorIoT Reduced Delays and the Initial Cost of Deploying Smart City IoT Solutions

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.

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Actility-AWS-Partners

How to Connect Your LoRaWAN Devices to AWS IoT Core Using Actility ThingPark 

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.

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Solutions-Architecture-1

Intelligent Video Analytics and Effective Remote Learning on Campus Private 4G/5G Networks

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.

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Cloud Anything-9

Onboarding and Managing Agents in a SaaS Solution – Using AWS IoT Core

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.

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TTI-AWS-Partners

Connecting Your LoRaWAN Devices from The Things Stack to AWS IoT Core

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.

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How to Deploy AI Inference on the Edge with the LG AIoT Board and AWS IoT Greengrass

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.

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Say Hello

Say Hello to 55 New AWS Competency, Service Delivery, Service Ready, and MSP Partners Added in August

We are excited to highlight 55 AWS Partners that received new designations in August for our global AWS Competency, AWS Service Delivery, AWS Service Ready, and AWS Managed Service Provider (MSP) programs. These designations span workload, solution, and industry, and help customers identify top AWS Partners that can deliver on core business objectives. AWS Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.

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Machine Learning-4

Using Fewer Resources to Run Deep Learning Inference on Intel FPGA Edge Devices

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.

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