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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 […]
Learn how enforcing a Unified Namespace (UNS) at the edge ensures reliable, structured data for live digital twins across any source, system, or protocol.
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.
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.
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.
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.
Industrial computing solutions specialist Dianomic Systems and embedded machine learning pioneer Boon Logic have announced a strategic partnership to deliver faster, more scalable anomaly detection for thousands of performance metrics across a wide range of industries, along with real-time data quality inspection before data is sent and stored in systems of record, operational systems or […]
Dianomic will deliver FogLAMP, its open source industrial IoT platform, on Google Cloud to help customers build edge applications that connect, buffer, and process machine data, and execute edge-based machine learning.
Optimizing machine operations using Industrial IoT Fledge with Google Cloud, ML and state-of-the-art digital twins and simulators
“Fledge” is an open-source framework used to implement predictive maintenance, situational awareness, safety, and other critical operations. Deployed in industrial use cases since early 2018, Fledge integrates IIoT, sensors, machines, ML/AI tools-processes-workloads, and cloud with the current industrial production systems and levels (ISA-95).
