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AWS Greengrass Hardware Enables Connectivity for IoT Edge Devices

By ·Categories: Industrial IoT·Published On: May 13th, 2022·6.3 min read·

AWS IoT solutions running on qualified AWS Greengrass hardware were created to address challenges faced by IT teams. The growth of IoT devices at the edge means IT teams have to manage thousands of Operation Technology (OT) network endpoints. How can it be done without significant investment in software development time?

Instead of spending hundreds of thousands or maybe even millions of dollars developing and maintaining a custom IoT device management solution, why not invest in an existing one?

Amazon Web Services (AWS) offers a suite of services for edge applications. Using AWS Greengrass hardware at the IoT edge can help you to effectively manage your endpoints in a scalable way and deliver actionable intelligence.

Check out our Tech Edge Video and continue reading below.

What is AWS IoT Greengrass?

AWS Greengrass is an Amazon Web Services (AWS) product designed to bring the power of the AWS cloud to IoT edge devices.

AWS allows those devices to: 

  • Respond to local events in real-time
  • Operate independently of a network connection
  • Leverage AWS cloud connected services
  • Be remotely monitored

It does all that while operating securely with the end-to-end encryption that AWS provides. Using local hardware like OnLogic’s line of AWS Greengrass certified PCs brings the power of the cloud to connected devices at the edge.

Diagram of AWS Architecture showing the idea of Connected Devices at the Edge

How does AWS Greengrass Work?

Greengrass works by using a locally deployed AWS IoT Greengrass Core, in our case an OnLogic Greengrass qualified computer, as a local data aggregator for your connected devices, sensors, or other local connectors. The Greengrass core communicates to local devices in their native protocol such as OPC-UA, LoRa, or Zigbee using AWS IoT Connectors.

Data is sent back to the cloud via MQTT, a lightweight messaging protocol, and then routed through AWS IoT Core, an AWS managed service for managing your device connections to the cloud. From there you can easily connect to AWS Services like Amazon S3, EC2, or Sagemaker depending on your application needs.

AWS IoT Greengrass and AWS Cloud Services for Smart City Projects

LOverhead photo showing traffic being monitored in a smart city solution using connected devices, like a surveillance camera, at the edgeet’s say you are the supervisor for a city road system. You want to optimize your traffic management systems to improve traffic flow by leveraging data. To reach your project goal to reduce congestion, you plan to deploy a series of AWS Greengrass-enabled embedded computers. Those computers will interact with connected devices at the edge, such as local sensors and other IoT devices out in the field, to make smarter, more informed decisions.

Artificial Intelligence (AI) with AWS Greengrass

Your first stop is looking at intersections. By deploying a Greengrass-enabled edge computer you can use local cameras to detect the number of cars waiting at an intersection and have traffic lights act in real-time on that data using machine learning (ML) inference. The result? You can reduce congestion and improve the driver’s experience by eliminating an unnecessarily long red light. You can also send data back to the AWS cloud to further train your machine learning model and improve device functionality for future traffic scenarios at that intersection. 

Since the application runtime is done locally on the device, you can send back the finished data to the cloud instead of a raw data stream. As a result, you save on transmission costs. Additionally, you can run the system offline if needed. That means that even if you have intermittent WAN connection, you can keep your systems running and collecting data.

IoT Analytics with AWS Greengrass

Wondering how you can leverage the AWS cloud with the traffic flow data you’ve created? AWS Lambda functions can be used to create, test, and run code without provisioning and managing servers. You can then update the runtime Lambda functions on your AWS Greengrass hardware, all without needing to do any additional updates. 

You can use AWS IoT Analytics to process, organize, and route data while making it available to other AWS services for use in applications like AWS Quicksight for data analytics.

Have 3rd party applications you want to tie in as well? OnLogic and AWS have you covered with our partners like EdgeIQ to add further functionality to your project.

What is EdgeIQ and How Does it Tie to Greengrass?

EdgeIQ is a platform designed to manage the lifecycle management and orchestration of your connected devices. OnLogic has partnered with EdgeIQ to bring a line of EdgeIQ-enabled embedded PCs to serve your application. EdgeIQ’s device lifecycle management allows you to onboard and provision devices with zero-touch deployment for EdgeIQ-enabled devices to automatically configure and boot on power-up. Whether you have 1,000 or 1,000,000 connected devices at the edge, EdgeIQ allows you to monitor and update devices all from a single pane of glass.

EdgeIQ screen shot to show how the software manages connected devices at the edge

Leverage AWS to Reduce Deployment Time

EdgeIQ also leverages data and application orchestration to help manage information flow for your IoT edge applications. Whether those Edge applications are built from the ground up or utilizing other platforms like AWS Greengrass, EdgeIQ can help seamlessly tie into those platforms. Using Greengrass means that IT resources are only a click away. That means you can reduce the time to make those resources available to your developers from weeks to just minutes. And, EdgeIQ natively integrates with AWS, Azure,  or your private cloud.

EdgeIQ as Part of a Traffic Management System

Back to your Smart City project. When your technicians go onsite to install an EdgeIQ enabled PC for your Greengrass application, all they need to do is plug in the PC, log into their AWS account and take advantage of zero-touch provisioning to automatically deploy software, Greengrass, and Lambdas. After this simple installation, you can manage a connected device’s uptime. That means you can react in real time to device wellness using EdgeIQ’s built in tools. Now, you can centrally manage everything from your traffic control center and accomplish your project goals while reducing cost and improving operating efficiency.

AWS Architecture diagram

Why use OnLogic’s Industrial Computers as part of your IoT Edge Solution?

The edge of your network is typically not a good location for an off the shelf traditional tower PC. The environment at the edge will most likely expose your system to dust, temperature, shock, vibration, variable input power, and other non-ideal conditions. OnLogic’s line of Industrial and Rugged PCs are the ideal hardware solution for AWS IoT Greengrass or EdgeIQ. All of our reliable and durable PCs are built to order. That means if you need an internal 4G modem for remote connectivity, serial ports for legacy device communication, or additional functionality, we’ve got you covered.

Watch our OnLogic Live – IQ at the Edge with AWS

We’ve invited our friends from EdgeIQ and Amazon Web Services (AWS) to talk about the challenges of the modern factory. Managing dozens, hundreds, or even thousands of devices at the edge is possible. Using IoT orchestration solutions at the edge and in the cloud, you can manage device networks of any size in a single pane of glass. The event was informative and entertaining and is available to watch on demand.

OnLogic Live: IQ at the Edge with AWS - link to watch on demand

Watch OnLogic Live On Demand

Ready to connect your devices at the edge with AWS IoT Greengrass? Contact our technical sales team today, or explore our online store.


Note: We originally posted this blog on September 10, 2020. We updated the content on May 13, 2021.

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About the Author: Cole Wangsness

Cole is the leader of strategic partnerships at OnLogic. He works to enable the technologies that customers to solve problems today and in the future through years of industry knowledge. When not working, he enjoys training his dog (she's 9, but he tries anyways).
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