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With digital twins and IIoT, you gain real-time insight, precision, and control, down to the smallest detail. See what’s otherwise impossible to see.
Digital twins are often described in abstract terms. But in reality, they’re something far more concrete. Digital twins are virtual replicas of physical systems that are continuously updated and used to monitor, simulate, and optimize performance. And this is where IIoT (Industrial Internet of Things) plays a key role. Without sensor data, there’s no digital life.Â
Think of a smartwatch that tracks your heart rate. It’s more than just a piece of hardware, it’s a kind of digital twin of your body and health status. In the industrial world, the same concept applies, only on a much larger and more complex scale.Â
A digital twin is essentially a virtual copy of a physical object or system, such as a wind turbine, an engine, or a bridge. But it only becomes truly valuable once it’s connected to real-time data from sensors via IIoT.Â
These sensors provide continuous insights into conditions, context, and activity. That makes it possible not just to monitor, but also to analyze patterns and predict issues such as wear, failure, or maintenance needs.Â
One example is our work on the Köhlbrand Bridge in Hamburg – a 4 km long piece of infrastructure from the 1970's that requires frequent maintenance. Under German law, bridges like this must be inspected every three years, often using traditional methods like tapping on the concrete with a hammer to detect internal weaknesses through sound.Â
We helped build a digital twin of the bridge, connected to sensors that monitor its condition continuously. The result is a kind of living X-ray, visualized through a 3D interface. It’s a bit like navigating through Google Earth, but with technical insight. This makes it faster and easier to identify which parts of the structure need attention, and may eventually reduce the need for manual inspections altogether.Â
Issues are detected earlier and can be resolved before they escalate.
Resources are used where they’re needed, not based on fixed schedules.
Data-driven analysis and simulations reduce human mistakes.Â
New team members get a quicker, more intuitive understanding of complex systems.
Digital twins are no longer just a vision of the future. They’re already here, and with IIoT as the data engine, they’re opening new ways to make complex physical systems more transparent, accessible, and efficient.Â