Building smart infrastructure: Using AWS services for digital twins

A digital twin is a digital replica of a physical asset or system, which can be used for various purposes including simulation, analysis, and optimization. In the government sector, digital twins can be particularly useful in optimizing the performance of essential infrastructure, such as transportation networks, power grids, and water systems. Services from Amazon Web Services (AWS), such as AWS IoT Core, Amazon Simple Storage Service (Amazon S3), and Amazon SageMaker can be used to collect and manage the vast amounts of data generated by internet of things (IoT) devices in smart infrastructures, store them, and generate insights through machine learning.

In this post, learn use cases for digital twins, plus how to create an open-source digital twin sample front-end application built with AWS Amplify, Amazon Cognito, and AWS IoT Core that you can use as a starting point for building efficient, scalable, and secure digital twin solutions.

AWS services for collecting and managing IoT data in smart infrastructure

Digital twins can be particularly useful in optimizing processes and sub-systems with connected infrastructure to make cities smarter and safer for citizens. It can also be helpful in other scenarios like transportation networks, power grids, and water systems. For example, if a digital twin model detects that a traffic intersection is experiencing heavy congestion, city officials can redirect traffic to other routes or adjust the timing of traffic signals to improve the flow of traffic.

Besides traffic management, digital twins can also be used in other areas of government operations, such as asset management and emergency response. By providing insights based on real-time data, a digital twin of a power grid can be used to visualize potential bottlenecks in energy distribution infrastructure to proactively address parameters that can lead to system outages, whereas a digital twin of a water treatment plant can contextualize  deeper data-driven understanding of the water treatment process flow to reduce water waste and losses, and support sustainable operations.

Overall, the use of digital twins in public sector operations can streamline process efficiencies, reduce operational costs, and improve service delivery to citizens. By using AWS IoT Core and Amazon S3, government agencies can store and analyze large amounts of data to make informed decisions.

Get started with digital twins on AWS with open source solutions

To make it simpler to get started with digital twins, AWS published an open-source example of a simple digital application on GitHub. With this, you can set up a digital twin using AWS services. The sample application includes a front end that allows users to interact with their digital twin and view real-time data from their physical asset, and it can be enriched and customized with little effort.

The digital twin is built using AWS Amplify, a framework that makes it simple to build scalable and responsive web and mobile apps. In this project, AWS Amplify is used in conjunction with Amazon Cognito User Pools and Amazon Cognito Identity Pools to provide user authentication and authorization for web and mobile applications. Amazon Cognito User Pools allow you to create and manage user directories, whereas Amazon Cognito Identity Pools enable you to grant access to AWS services based on the authenticated user’s identity.

Figure 1. Example web application front end for a digital twin of a car.

The sample application also makes use of the AWS IoT Core Device Shadow feature, which enables you to store, retrieve, and update the state of a device, even when it’s disconnected. With AWS IoT Core, you can maintain a “shadow” copy of your device’s desired state and reported state in the cloud, enabling you to synchronize the device with the latest desired state and react to the changes in the reported state. To send data to AWS IoT Core, the physical asset, such as a machine or sensor, needs to be connected to the internet and configured for data exchange. This can be done in various ways, including using AWS IoT Greengrass, an open-source edge runtime and cloud service that helps you build, deploy, and manage intelligent device software for devices that are located on premises, at the edge of a network, or in a remote location. With AWS IoT Greengrass, you can locally compute data, process messages, perform data caching, and run machine learning (ML) inference capabilities at the edge. It enables you to keep your devices and the cloud in sync and respond to the data generated by your devices in near real time, even when they’re disconnected from the internet.

A starting point for building efficient, scalable, and secure digital twin solutions

Figure 2. Use the sample application to get started with digital twins and customize it to your needs.

To get started with the sample application, you can clone the GitHub repository and follow the instructions provided in the README file. The sample application includes detailed documentation and sample code to help you set up and configure a digital twin front end application for your environment. The solution can be set up in under an hour.

If you’re looking for a more comprehensive solution with more features, look to AWS IoT TwinMaker. The service allows you to use your existing IoT, video, and enterprise application data and combine it with existing 3D models to create virtual representations of any physical environment. AWS IoT TwinMaker is best suited for scenarios where you want to combine existing 3D models with real-world data, while the solution described in this blog post is suitable for situations where you need to build simple visual models for non-complex workflows.

Conclusion and next steps

In conclusion, this sample application is a starting point for organizations looking to implement a digital twin. By using this sample application, you can set up a digital twin and start optimizing your operations. Using AWS Amplify and AWS IoT Core, organizations and agencies can build a digital twin that is responsive, scalable, and secure. The presented sample can be customized by changing the React Front-end code from the repository. It comes with some boilerplate code to retrieve updates from AWS IoT Core Device Shadow and new properties can be added to the front end.

As a next step, start exploring AWS IoT Twin Maker, which provides scalability, improved data management, and advanced analytics for large IoT twin projects. It simplifies and streamlines the process of managing IoT devices and twins with automated workflows and robust security features. By leveraging these features, you can further optimize your IoT twin project for increased efficiency, scalability, and security, supporting your IoT devices and twins in operating at peak performance.

Read related stories on the AWS Public Sector Blog:

• Using AWS IoT TwinMaker to build a spacecraft digital twin
• 5 public sector technology predictions for 2023

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