Industrial Edge Controller | Products

Overview

Industrial Edge Controller is a ruggedised, fanless industrial PC that runs Docker / Kubernetes containers next to the machine, performs AI inference on the production line, and closes a real-time control loop with sub-millisecond determinism. One box replaces the traditional "PLC + edge gateway + vision PC + protocol converter" quadrumvirate that clutters most modern cells.

Built for plants modernising beyond classic PLCs — vision-guided pick & place, predictive maintenance with ML, real-time energy optimisation, OPC UA aggregation, and tight integration with the cloud GitOps pipeline that engineering teams already use. Linux-based, container-native, and managed from a central fleet console.

Container-native — Docker / Podman / k3s lightweight Kubernetes
AI inference at the edge — ONNX / TensorRT / OpenVINO on optional GPU or NPU
Real-time co-located — Xenomai / PREEMPT_RT kernel for hard real-time loops
GitOps managed — Argo CD / Flux push updates to a fleet of hundreds of edges

How It Works

A real-time Linux kernel hosts a normal Docker / k3s runtime alongside a hard-real-time scheduler. Field protocols and control loops live in privileged real-time containers; everything else — AI inference, dashboards, telemetry — runs as standard pods. Cloud GitOps deploys new versions; failures auto-rollback.

Real-time core — isolated CPUs pinned to the RT scheduler with sub-millisecond jitter
Field I/O — Modbus, Profinet, EtherCAT, OPC UA, GigE Vision direct to hardware
Inference pipeline — cameras / sensors → preprocess → AI model → control decision
Container fleet — k3s manages pods, restarts on crash, rolls back on health-check fail
Cloud orchestration — Argo CD watches the Git repo and reconciles the entire fleet

Features

Hard real-time — PREEMPT_RT kernel, isolated cores, < 100 µs typical jitter
GPU / NPU options — NVIDIA Jetson, Intel Arc / Movidius, Hailo-8, Coral Edge TPU
Cyber-resilient — TPM 2.0, secure boot, encrypted disk, signed container images
OTA / GitOps — declarative updates, canary rollouts, automatic rollback
Standards-based — OPC UA Server / Client, MQTT 5, REST, Sparkplug B
Observability — built-in Prometheus exporters, OpenTelemetry traces, Loki logs
Vision-ready — GigE Vision, USB3 Vision, MIPI camera inputs with hardware sync
Fanless design — passive cooling for dusty / vibrating environments, 24/7 duty

Use Cases

Vision-based quality inspection — YOLO / Mask-RCNN on the line at 30 FPS, reject lane control
Predictive maintenance — vibration / current pattern recognition, raise ticket before failure
Energy optimisation — closed-loop control of HVAC, compressed air, chillers using ML setpoints
Robot guidance — 3D / 2D vision feeding robot trajectories in real time
Process aggregation — one edge controller per cell talking OPC UA up to plant SCADA
Edge digital twin — high-frequency mirror of the physical asset for what-if simulation

Specifications

CPU: Intel Xeon-D 8-core / Intel Atom x6000 / NVIDIA Jetson AGX Orin options
Memory: 8 / 16 / 32 / 64 GB DDR4 ECC, 256 GB to 2 TB NVMe
GPU / NPU: optional NVIDIA RTX A2000, Hailo-8L 26 TOPS, Coral 4 TOPS
OS: Ubuntu Core / RHEL / Yocto with PREEMPT_RT, k3s 1.28, Docker 24
Ports: 2–4× 2.5G Ethernet, 4× USB 3, DP/HDMI, RS-485, CAN, 4-DI/4-DO
Power: 24 VDC ±20 %, 25–80 W typical, optional redundant input
Environment: −25 to +60 °C, IP30, fanless, 5 g vibration, M12 / M8 connector options
Security: TPM 2.0, secure boot, FIPS 140-2 crypto, signed firmware, role-based SSH