Power Quality Monitoring with Edge AI
Monitoring electrical current and voltage waveforms to detect anomalies in power distribution systems. Identifies power surges, harmonics, phase imbalances, and degradation patterns using lightweight time-series models on current sensor data sampled via ADC. Deployed on MCUs connected to current transformers or Hall-effect sensors on electrical panels. Enables early detection of electrical faults before they cause equipment damage or safety hazards.
Hardware Requirements
| Minimum RAM | 32 KB |
| Minimum Flash | 256 KB |
| Sensor Inputs | current |
| Typical Model Size | 15 KB (quantized int8) |
| Minimum Clock | 48 MHz |
Hardware Guides
No hardware guides for power quality monitoring yet. Use the MCU Checker to find compatible hardware.
Industry Applications
Orchestrate Power Quality Monitoring with ForestHub
Your devices run power quality monitoring on-device. ForestHub on your Linux edge gateway ingests their results over MQTT/Modbus/OPC-UA, orchestrates the sense-reason-act loop as an auditable graph, and acts on the line — the LLM is one node among many.