Industry executives and experts share their predictions for 2023.  Read them in this 15th annual VMblog.com series exclusive.

Real-Time Digital Twins and Simulation To Thrive in 2023

By Dr. William Bain, CEO and Founder of ScaleOut Software

Many businesses and government agencies are tasked with managing complex webs of real-world entities that need to be continuously tracked and analyzed to keep operations running smoothly. Whether it's a large vehicle fleet delivering packages, a network of power transmission lines and substations, IoT sensors distributed throughout a city, or a population of smart watches for health tracking, the need is widespread and urgent.

The answer to tackling these complex challenges increasingly appears to lie in the technology of digital twins. Traditional digital twins have been used as virtual models of physical devices, like jet engines, intended to capture their essential behaviors and assist in design over their life cycles. However, a new approach has emerged that uses digital twins for real-time analytics to capture telemetry from the physical world, enrich it with contextual information, and provide immediate analysis as well as simulation. Called "real-time digital twins," this exciting new technology is expected to thrive in 2023. Here's more detail on what the future may hold.

Developers and Businesses Will Adopt Real-Time Digital Twins to Extract Deeper Operational Intelligence

Moving beyond their use in developing new products, digital twins are now able to track dynamically evolving state information in real time for thousands of individual IoT data sources. Called "real-time digital twins," they provide an important breakthrough for streaming analytics. The use of per-device state information enables deep introspection within milliseconds and more effective feedback than previously possible. Unlike traditional techniques for stream processing, real-time digital twins provide insights that can be utilized immediately rather than having to wait for offline data analysis. For example, they can track a large vehicle fleet to identify lost or fatigued drivers and emerging mechanical issues. They also can track thousands of IoT sensors in a power grid, corporate infrastructure, or smart city to immediately identify and evaluate security threats.

More organizations and developers will adopt real-time digital twins in 2023 to meet their widespread real-time device monitoring needs. From tracking smart watches to ensuring the timely distribution of supplies after a disaster, the applications are near limitless. Being able to obtain effective real-time insights in complex scenarios will become increasingly critical in quickly making informed decisions. As real-time digital twins continue to gain intelligence, they are poised to deliver significant new capabilities for streaming analytics.

Real Time Simulation with Digital Twins Will Become an Important Tool

At the same time, digital twins will enable the simulation of live systems to help organizations across numerous industries validate complex real-time interactions and identify issues. This will provide an important new technique for tracking live systems faster than real time and making projections that enable key optimizations.

For example, digital twins can simulate thousands of data sources, such as passengers within a large transportation system or components within a municipal water and power infrastructure to predict behaviors that must be mitigated. They also can collect telemetry from live systems and replay this telemetry in simulation to evaluate alternative outcomes and optimize real-time monitoring.

As developers and organizations face increasing demands to better manage their complex live systems, the use of digital twins in simulating real-time systems will offer a powerful tool for modeling behavior, improving real-time analytics, and making predictions. In 2023, we expect this novel combination of technologies to offer new insights that were not previously possible.

##

ABOUT THE AUTHOR

Dr. William Bain is the founder and CEO of ScaleOut Software, which develops software products to provide operational intelligence for live systems using scalable, in-memory computing. Bill earned a Ph.D. in electrical engineering from Rice University. Over a 40-year career focused on parallel computing, he has contributed to advancements at Bell Labs Research, Intel, and Microsoft, and holds several patents in computer architecture and distributed computing.