Early Industry 4.0 efforts focused mainly on connecting devices, but today’s AI, machine learning, and digital twin applications require high-quality, full-bandwidth data to reach IT systems – not just the control layer.
HBK supports this shift with edge-based measurement systems that provide parallel IT and OT connectivity, so real-time control and full-bandwidth measurement data can be used across both industrial and enterprise environments.
Traditional OT systems still receive data through industrial fieldbuses and analogue interfaces. At the same time, calculated values and full-bandwidth measurement data are sent in parallel to IT systems through open standard protocols such as MQTT, OPC-AU and openDAQ™.
This enables direct access to high-quality process data at the source. It can be used in IT environments such as cloud platforms, analytics tools, and MES systems, while also enabling real-time analysis, AI and ML model training, and digital twin applications – without disrupting control loops or adding integration complexity.
This architecture allows real‑time production data to be used at the same time for control, monitoring, optimisation, and long-term initiatives such as AI‑driven process improvement and digital factory integration.
Smart sensors and digital-ready devices generate high-resolution, full-bandwidth measurement data.
Edge electronics convert raw sensor signals into structured, real-time process data at the source.
While edge systems provide full-bandwidth data and advanced processing, certain applications benefit from distributed intelligence inside the sensors themselves.
CAN‑MD-based smart sensors perform local data reduction and diagnostics before data reaches the edge layer. This approach complements traditional edge processing by optimising bandwidth usage and enabling scalable monitoring architectures, especially in distributed or mobile systems.
Open interfaces connect measurement data directly into industrial control systems.
Measurement data extends into IT systems for visibility and optimisation.
This architecture allows real‑time production data to be used at the same time for control, monitoring, optimisation, and long-term initiatives such as AI‑driven process improvement and digital factory integration.
MQTT, REST or OPC-UA The protocol you choose shapes how effectively machines, sensors and IT systems work together. This white paper explains the strengths of each—and how to combine them for secure, scalable IT/OT connectivity from the shop floor to the cloud.
IT/OT connectivity means linking operational technology (OT) – like sensors and PLCs – with information technology (IT) systems such as cloud platforms, MES and analytics tools. It allows real-time measurement and production data to flow from machines into IT environments to support digitalisation and better decision-making.
IT/OT integration is essential for Industry 4.0 because it lets production data flow beyond control systems and into IT tools used for analytics, optimisation and automation. Without this connection, manufacturers cannot fully use real-time data, AI, machine learning or digital twin technologies.
OT data is typically used for real-time machine and process control, such as PLC signals. IT data is used for analysis, reporting, optimisation and business decision making. Modern industrial connectivity makes it possible for the same measurement data to serve both purposes at the same time.
Edge-to-cloud connectivity processes data locally at the machine (the edge) or system level before sending selected data to cloud or enterprise systems. This reduces latency, supports real-time decisions, and allows full-bandwidth measurement data to be used for analytics, AI and monitoring without overloading central systems.
Sensor-to-cloud integration gives direct access to high-quality measurement data from the source. This supports real-time monitoring, predictive maintenance and process optimisation, while also reducing integration complexity and improving data consistency across the organisation.
Industrial data can be standardised by structuring it at the source and using open communication protocols such as MQTT or OPC UA. This ensures consistent data formats across machines, simplifies system integration, and supports scalable digital architectures across multiple production sites.
IT/OT connectivity enables digital twins and AI by providing continuous access to high-quality, real-time measurement data. This data is essential for running accurate simulations, training machine learning models, and improving process performance, all without interrupting production.
This will bring together HBM, Brüel & Kjær, nCode, ReliaSoft, MicroStrain and Discom brands, helping you innovate faster for a cleaner, healthier, and more productive world.
