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Digital Twin - What is the Future?

As companies continue to aggressively pursue smart sensor technology and Internet of Things (IoT) technology, analyses and visualization of the data collected from the sensors can be combined with augmented and virtual reality technology. Because of the incoming data collected through digital twins, utilizing a virtual or augmented experience is the best way to digest the information and the results gained from digital twins are collected from the performance of simulations. AR/VR provides convenience and a sense of reality to the data obtained and compliments the benefits provided by digital twin technology.

With an estimation of 25 billion connected global sensors by 2021, digital twins will soon exist for millions of things including a jet engine, a human heart, even an entire city that mirrors the same physical and biological properties as the real thing. The implications are extreme, real-time assessments and diagnostics much more precise than currently possible, repairs executed at the moment, and innovation that is faster, cheaper, and more logical.

What is Digital Twin

It is a computer program that takes real-world data about a physical object or system as inputs and produces as outputs’ predictions of how that physical object or system will be affected by those inputs. The twin could also be designed based on a prototype of its physical counterpart, in which case the twin can provide feedback as the product is refined; a twin could even serve as a prototype itself before any physical version is built.


Digital twinning capabilities has accelerated manifold due to a number of factors :

  • Interoperability. Over the past decade, the ability to integrate digital technology with the real world has improved exponentially. The majority of this improvement is because of enhanced industry standards for communications between IoT sensors, operational technology hardware, and vendor efforts to integrate with diverse platforms.

  • Visualization. The data required to create digital twin simulations can complicate analysis and make efforts to gain meaningful insights, challenging. Advanced data visualization can help meet this challenge by filtering and distilling the information in real time. The latest data visualization tools go far beyond basic dashboards and standard visualization capabilities to include interactive 3D, VR and AR-based visualizations, AI-enabled visualizations, and real-time streaming.

  • New sources of data. Data from real-time asset monitoring technologies such as LIDAR (light detection and ranging) and FLIR (forward-looking infrared) can now be incorporated into digital twin simulations. Similarly, IoT sensors embedded in machinery or throughout supply chains can feed operational data directly into simulations, enabling continuous real-time monitoring.

  • Instrumentation. IoT sensors, both embedded and external, are becoming more accurate, cheaper, and more powerful. With improvements in networking technology and security, traditional control systems can be leveraged to have more granular, timely, and accurate information on real-world conditions to integrate with the virtual models.

  • Simulation. The tools for building digital twins are growing in power and sophistication. It is now possible to design complex simulations, backtrack from detected real-world conditions, and perform millions of simulation processes without overwhelming systems. Further, with the number of vendors increasing, the range of options continues to grow and expand. Finally, machine learning functionality is enhancing the depth and usefulness of insights.