AWS IoT TwinMaker Optimizes the Build of Digital Twins

By Saumitra Jagdale

Freelance Technology Writer

December 21, 2021

Blog

AWS IoT TwinMaker Optimizes the Build of Digital Twins

Amazon Web Services recently announced its IoT TwinMaker that optimizes the development of digital twins, making the complex process much faster and easier. AWS IoT allows developers to construct and use digital twins of real-world systems to monitor and optimize operations more quickly and easily.

Gartner Inc. recognized Digital Twin Technology as one of the top 10 key technology trends for 2017. Every industrial product will have a dynamic digital representation under the Digital Twin idea, which depicts the confluence of the physical and virtual worlds. Organizations may have a comprehensive digital footprint of their products throughout the product development life cycle.

Credits: AWS

The AWS IoT TwinMaker is much faster than conventional digital twin APIs as it allows the use of existing IoT, video, and enterprise application data without reingesting or moving it to a new place. AWS IoT TwinMaker provides the tools needed to create digital twins in order to improve building operations, production output, and equipment performance.

It supports users employing digital twins to generate a comprehensive perspective of your operations faster by:

  • Combining existing data from numerous sources
  • Creating virtual representations of any physical location
  • Combining current 3D models with real-world data

Credits: AWS

To properly simulate a real-world environment, AWS IoT TwinMaker creates a digital twin graph that integrates and understands the links between virtual representations of the physical systems and linked data sources.

The users can further visualize the data in the context of the physical environment after the creation of the digital twin graph. Users can then add dynamic video and sensor data overlays from linked data sources, insights from connected machine learning (ML) and simulation services, and equipment maintenance records and manuals to build a spatially-aware picture of the operations.

The AWS IoT TwinMaker offers its users various built-in data connectors for numerous AWS services including AWS IoT SiteWise for equipment and time-series sensor data; Amazon Kinesis Video Streams for video data; and Amazon Simple Storage Service (S3) for visual resources and data from business applications. Moreover, the AWS IoT TwinMaker proves to be of great help in designing custom data connections to use with other data sources like Snowflake and Siemens MindSphere.

Additionally, the AWS IoT TwinMaker has an Amazon Managed Grafana plugin to assist developers in creating a web-based application for end-users. It provides a low-code experience for building user-friendly UIs to effectively monitor and interact with the digital twins. Grafana is multi-platform open-source analytics and interactive visualization web application that is utilized by end-users such as plant operators and maintenance engineers to view and work with the digital twin in order to enhance factory operations, boost production output, and improve equipment performance.

Amazon-managed Grafana is a fully managed solution for Grafana Labs' open source dashboard and visualization platform.

The AWS IoT TwinMaker saves time with a knowledge graph that connects your data sources to virtual representations of physical systems to properly simulate real-world situations. Moreover, it offers immersive 3D pictures of the systems and processes to boost efficiency, productivity, and performance. Hence, its numerous use-cases that include increasing equipment uptime in remote facilities and enhancing the tenant experience in commercial buildings.

The AWS IoT TwinMaker is a game-changer in the digital twin domain. You can refer to the resources provided by AWS for more information.

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Saumitra Jagdale is a Backend Developer, Freelance Technical Author, Global AI Ambassador (SwissCognitive), Open-source Contributor in Python projects, Leader of Tensorflow Community India, and Passionate AI/ML Enthusiast.

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