AWS IoT TwinMaker allows developers to integrate data from multiple sources like equipment sensors and video cameras and combines that data to create a knowledge graph that models the real-world environment.
Amazon Web Services (AWS) has announced the general availability of a service that aims to make it faster and easier for developers to create digital twins of real-world systems like buildings, factories and industrial equipment.
The service was announced at the AWS Summit San Francisco. AWS said in a statement that there are no upfront commitments or fees to use AWS IoT TwinMaker, and customers only pay for accessing the data used to build and operate digital twins.
Traditionally, to build digital twins, customers must manually connect different types of data from diverse sources, then create a knowledge graph that provides common access to all the connected data and maps the relationships between the data sources to the physical environment. To complete the process, they have to build a 3D virtual representation of their physical systems and overlay the real-world data on to the 3D visualisation – and then ensure the digital twin is kept up-to-date as conditions change.
The AWS IoT TwinMaker allows developers to integrate data from multiple sources like equipment sensors, video cameras, and business applications, and combines it to create a knowledge graph that models the real-world environment.
AWS IoT TwinMaker contains built-in connectors for Amazon Simple Storage Service, AWS IoT SiteWise, and Amazon Kinesis Video Streams (or customers can add their own connectors for data sources like Amazon Timestream, Snowflake, and Siemens MindSphere) to make it easy to gather data from a variety of sources.
“Sensors for equipment, buildings, and industrial processes are proliferating and generating massive amounts of data. Customers are increasingly eager to use that data to optimise their operations and processes”
The knowledge graph combines and understands the relationships of the connected data sources so it can update the digital twin with real-time information from the system being modelled. Customers can import existing 3D models – such as CAD and BIM files – directly into AWS IoT TwinMaker to easily create 3D visualisations of the physical system and overlay the data from the knowledge graph on to the 3D visualisations to create the digital twin.
Once the digital twin has been created, developers can use an AWS IoT TwinMaker plugin for Amazon Managed Grafana to create a web-based application that displays the digital twin on the devices used to monitor and inspect facilities and industrial systems.
He added: “With AWS IoT TwinMaker, customers can now derive previously unavailable insights about their operations that inform real-time improvements to their buildings, factories, industrial equipment, and production lines, and make accurate predictions about system behaviour with minimal effort.”
AWS IoT TwinMaker is generally available in US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Europe (Frankfurt), and Europe (Ireland) with availability in additional AWS regions coming soon.