Edge Computing (Industrial)
Industrial edge computing processes data locally at or near the machine, rather than sending everything to the cloud. It enables low-latency control, reduces bandwidth, and keeps sensitive data on site — useful for real-time analytics and predictive maintenance.
By running analytics and AI models close to the equipment, edge computing gives fast responses for control and monitoring even with limited or intermittent connectivity, and cuts the cost of moving large sensor streams to the cloud. Many industrial AI deployments use a hybrid model: edge for real-time inference, cloud for training and fleet-wide analysis.
Related reading
- Predictive maintenance: a practical guide
- Cognite Data Fusion
- Proficy
- Industrial IoT (IIoT)
- Industry 4.0
- OPC UA
Related terms
Industrial IoT (IIoT) · Industry 4.0 · OPC UA · Anomaly Detection · Edge AI
Related guides
Software
Cognite Data Fusion
Industrial DataOps and contextualisation platform; being acquired by Schneider Electric.
Proficy
MES, historian and digital-twin tooling for manufacturing; divested by GE Vernova in 2026.
Where this applies
State of Industrial IoT & Connectivity 2026 · Humanoid robots enter production · Industrial-scale AI model distillation