Author: Natalie Jaeger
Semantic Modelling: The Secret to Scalable, Modular Digital Twins
What is semantic modelling? Semantic modelling is the process of gathering all the relevant data and modelling tools for a small scale mathematical or ML/AI model in one place, and building a small scale model which can be used in conjunction with similar models to build a larger scale model of a system. This modular
Enforcing a UNS: Reliable, Usable Data from Any Source to Any Space
Learn how enforcing a Unified Namespace (UNS) at the edge ensures reliable, structured data for live digital twins across any source, system, or protocol.
From Condition Monitoring to Real-Time Control: The Power of Live Feedback Loops
Until recently, it has not been possible in many cases to fully understand such complex systems, and thus to ensure that optimal performance is maintained without unacceptable safety risks. This is where live digital twins can help. For the first time, engineers and operators can have a full picture of machine behaviour in real time. This means not only are the insights from traditional condition monitoring systems replicated in the twin, but a far deeper understanding of what the machine is doing is possible.
Why Your Digital Twin Needs an Intelligent Data Pipeline
Live digital twins need more than basic data connectors. Intelligent data pipelines offer real-time, multi-source input, edge processing, and smart routing for faster and more accurate insights than legacy methods like MQTT or OPC UA.
What Is a Live Digital Twin? (And Why the Old Ones Aren’t Enough)
At its most basic, a digital twin is a virtual representation of a real world system. This is done so that a better understanding can be gained of how the system works. A live digital twin, and as the name suggests, it’s very much like a digital twin, except it uses live streaming data, and calculates live.
Introducing FogLAMP Suite 3.0 – Live Digital Twins
Dianomic’s FogLAMP Suite 3.0 delivers live digital twins through intelligent industrial data pipelines unifying real-time data from machines and sensors for both brownfield and greenfield deployments. Unlike cloud-only data pipelines, FogLAMP establishes a plant-wide data fabric, ensuring secure, normalized streaming data flow between the plant floor and cloud. This empowers AI-driven applications, digital twins, and OT/IT convergence. With features like role-based access control and flexible development tools, FogLAMP facilitates seamless collaboration and empowers both IT and OT teams to optimize operations and drive innovation with unprecedented speed and precision.