Learn how real-time digital models, powered by intelligent data pipelines and semantic modeling, are transforming condition monitoring, system optimization, and operational control at scale.
Many digital twins operate on delayed or periodic data, limiting their usefulness for real-time decision-making. Live digital twins are different: they continuously sync with physical assets using real-time data streams. This allows for real time actions from real time data, critical in high-stakes industrial environments.
Legacy connectors are rigid, source-destination specific, and difficult to scale. Intelligent data pipelines, on the other hand, provide many-to-many connectivity across sources and destinations, support inline data transformation, and enable real-time sensor fusion. This unlocks more accurate models, lower latency, and a foundation for true live twin performance.
Semantic models compartmentalize machines and processes into manageable units. Each with its own data, logic, and behavior. This modular architecture allows teams to build digital twins incrementally, isolate issues quickly, and scale systems across plants or processes without rewriting core logic.
Modern digital twins must do more than monitor, they must act. This whitepaper outlines how to manage data pipelines that support both cloud-based model training and low-latency, edge-based inference. Learn how to enable set point control, trigger-based optimization, and live ML feedback loops. All from the same architecture.
Stop wrestling with complicated systems and data silos.
FogLAMP Suite 3.0 makes it easy to connect, normalize, and stream data across your entire plant. Gain real-time visibility and control while saving time and resources.
