AI System for Edge Analytics via IoT Gateways
Edge analytics — data processing closer to source, on gateway, not in cloud. IoT gateways with ML: cloud traffic reduction 10–100×, latency <10 ms instead of 100–1000 ms, operation when connection lost.
Hardware Platforms for Edge Gateway
Industrial:
- Advantech ARK, MIC series — ruggedized x86, Intel Atom/Core, optional FPGA
- Siemens IPC — integration with Simatic ecosystem
- HMS Anybus Edge — industrial protocol connectivity + Linux edge
General Purpose Edge:
- NVIDIA Jetson Orin NX (16–64 GB) — best AI performance/power balance for non-hazardous zones
- Intel NUC 13 Pro + OpenVINO — optimized for Intel Neural Stick / Movidius
- Raspberry Pi 5 + Hailo-8 accelerator — budget option up to 26 TOPS
Edge ML Functions on Gateway
Local Filtering & Aggregation: Raw data (1000 samples/sec) → edge ML → only anomalies and aggregates to cloud (5–10 measurements/min). Traffic reduction 99%.
Real-time Anomaly Detection: Streaming anomaly detection: Z-score, IQR, Isolation Forest. Immediate alert on critical deviation without cloud round-trip.
Event Detection: Threshold alerts → ML event detection. Distinguish real anomaly from noise.
Orchestration
Azure IoT Edge / AWS IoT Greengrass / Balena.io for remote management of ML modules on gateways. OTA model updates.