When Digital Twins Get AI-Powered 6G

When digital twins get 6G, what will they be like?

The sixth generation of wireless technology is expected to emerge in the late 2020s.
Building on the 5G networks that are gaining prominence today, 6G networks promise to be significantly faster and smarter than today’s technology.

With the emphasis on seamlessly connecting systems and IoT devices, AI-powered 6G’s impact on digital twins and other Industry 4.0 technologies could be significant.

How fast is 6G compared to 5G?

While 5G’s peak data rates up to 20gbps, 6G is expected to deliver rates of 1 terabit per second.

This means 6G will be capable of downloading and streaming data and communicating at speeds up to 50 times faster than its predecessor.

4G and 5G networks that digital twins rely on today can restrict the volume of data processed in real-time, delaying response times for complex analyses.

Data Processing

With ultra-high bandwidth and near-zero latency, 6G will enable digital twins to process vast amounts of data from sensors and IoT devices in real-time.

That data will be instantly analyzed with AI algorithms, enabling immediate adjustments and optimizations for complex systems.

The enhanced data processing will significantly level up the predictive accuracy of digital twins.

Predictive Actions

They’ll be able to foresee maintenance needs, production issues, and supply chain disruptions with much greater precision and lead time than today.

Right now, digital twins can simulate scenarios and suggest optimizations.

They often require human intervention for decision making and execution.

Digital Twin Autonomy

With parallel advancements in AI and wireless technology, tomorrow’s digital twins won’t be hand wringers.

Instead of just identifying needs for adjustments, they’ll implement changes in production processes and maintenance schedules on their own.

With predefined parameters, the need for human intervention will be minimized.
Comprehensive integrations will expand future digital twinning use cases far beyond the maintenance and optimization applications they’re primarily used for today.

6G’s emphasis on connecting everything will enable a more coordinated and efficient approach to optimizing all stages of a product lifecycle, from design and production to supply chain management to end-of-life disposal.

While collaboration and remote operations with today’s digital twins are possible, applications can be limited by data transmission speeds and latency.

Transformative for Global Manufacturing

The ability for experts to interact with and manage manufacturing processes from anywhere in the world without a perceivable delay could be immensely transformative for global manufacturers.

Today, digital twins help drive sustainability KPIs by optimizing processes and reducing waste, but their potential is far from fully realized.

AI-powered 6G digital twins will unlock considerable energy savings and waste reduction with the ability to process and analyze more comprehensive data sets in real-time.

Ongoing Investments and Research

A 2022 joint research report from Nvidia and Heavy.ai proposed a framework for uniting digital twins with 6G networks.

The authors conclude, “The fast growth of network scale towards 6G and the stringent performance requirements of diverse use cases call for innovation tool and platforms.”

Though speculating about 6G-fueled applications may seem premature, telecommunications providers, global organizations and governments are already heavily investing in research.

Writing in Tech Radar, Dr. Christoph Dietzel, global head of products and research at DE-CIX, noted, “Concepts such as autonomous vehicles, smart cities or Industry 4.0 used to be far-off thought experiments.”

Thanks to 5G’s ongoing evolution, paired with advances in AI, machine learning, cloud computing and related technologies, the concepts are rapidly becoming mainstream.
The United Nations’ telecoms agency, the International Telecommunication Union, plans to finish the initial 6G standardization process no later than 2030, according to MIT Technology Review.