What are Digital Twins? And What’s the Next Evolution?
Simply defined, digital twins are virtual representations of physical objects. Whether duplicating a machine (like how every Tesla has a digital counterpart to allow for closer monitoring of systems), or a real-world process (like the tracking of changing traffic lights at an intersection), digital twins are created by streams of real-time data.
Of course, digital twins aren’t a new concept, but recent innovations have sparked renewed interest in them and their feasibility. The increased implementation of digital twins has allowed them to escape the confines of only being associated with IoT technologies and enter a broader range of applicability.
Digital twins have been and will continue to be important because they promise real-time observability—an asset businesses can harness to make better decisions faster, increase efficiencies, and more.
Swim enables end-to-end streaming from digital twins all the way to browser-based UIs and decision automation processes to make real-time observability possible.
The History of Digital Twins
The digital twin isn’t a new concept — but how we’ve defined and thought about them has evolved over the past few decades.
The idea of digital twins stemmed from the 1960s when NASA used basic twinning ideas as they began space exploration. Following the Apollo 13 disaster in 1970, scientists wanted a way to build digital models of spacecraft to run simulations. Although the technology of the time limited engineers as to what they could create, the idea of “twinning” continued to gain popularity as it spread to other industries.
In the early 2000s, GE made the Industrial Digital Twin popular, as digital twins became associated with product lifecycle management. This popularity led to a new interpretation of the concept. GE now defines digital twins as “unique software representations of individual assets, systems, or processes that enable companies to achieve improved business outcomes.”
How Digital Twins are Used Today
Today, digital twins are considered an industry-agnostic tool that companies can use for various use cases. Digital twins can simplify how real-world objects are managed and coordinated. Combined with machine learning, digital twins can enable predictive maintenance for industrial equipment or support personalized care in a healthcare setting.
Even healthcare providers and pharmaceutical companies utilize digital twins to model patients’ genome code, physiological characteristics, and lifestyles. The information collected allows healthcare companies to create personalized care plans for their patients, such as unique medications.
When it’s not cost-effective to build a replica of an object (think an airplane, a jet engine, or electrical equipment), digital twins provide companies with a digital copy, allowing them to test design changes without investing time and money in a physical reproduction.
How Swim Uses Digital Twins
At Swim, we define a digital twin as a software representation of a physical object or digital entity, such as a machine, sensor, geolocation, or point of sale history. Because of their flexibility, digital twins can be used in many industries — as long as they exhibit real-time observability. However, companies that use digital twins to model real-world entities today are essentially just providing a mirror that shows a virtual abstraction of the real world.
At Swim, we take digital twins one step further. Our digital twins provide real-time observability of an associated entity– but they also enable the capability to take action on the underlying entity.
While digital twins usually only reflect the state of the underlying entity, at Swim, they can also accept commands that drive state transitions within the underlying entity by invoking operations. When a digital twin switches from passive to active, it becomes known as a Web Agent. Web Agents are what act on the actual, physical device.
Web Agents allow the digital twins to execute real-time business logic as streaming data flows directly through the twin. Perhaps even more impactful, digital twins can coordinate with other digital twins, providing an additional communication layer.
The Swim platform allows companies to push streaming data all the way through the application stack without stopping the flow of data. Streaming data represents what’s actually happening in the real world right now — precisely what digital twins are designed to model.
Getting Started with Digital Twins
Digital twins are the ideal place to perform real-time computations. By nature, they partner well with streaming applications and streaming data because digital twins must constantly reflect the state of the physical or business entity they represent.
The Swim Platform is responsible for simplifying application creation and maintenance, while the Digital Twin is a core use case. We use digital twins to optimize and alleviate the data overload created by industrial devices and sensors.
Are you looking to transform your flood of data into actionable business insights? We can help. Explore our Swim Open Source and start developing applications using streaming data today.
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