AI‑driven electrical fault detection · Real‑time energy monitoring · Groq LLM reasoning
View Live Demo ExploreIndustrial electrical systems fail silently — wasting energy, destroying equipment, and endangering lives.
Conventional protection misses intermittent arcs, insulation decay, and overload patterns. Our AI fuses high-frequency sensor data with Groq LLaMA 3.3 70B reasoning to detect micro‑faults before they escalate. We cut energy waste by up to 30% and eliminate arc‑flash hazards through predictive severity classification.
High‑frequency waveform analysis & pattern recognition for series arc, ground, and incipient faults.
Real‑time consumption breakdown, harmonic distortion, and anomaly detection with sub‑meter accuracy.
Multi‑class risk levels (critical/warning/info) using Bayesian inference & Groq LLM reasoning.
Natural language root cause analysis & repair suggestions generated by fine‑tuned LLaMA 3.3.
3D real‑time visualization of grid health, event timelines, and predictive alerts.
Seamless data flow from on‑site sensors to Hugging Face Spaces for continuous learning.
From raw signal to actionable intelligence – low‑latency AI inference at scale.
Inference at 500+ tokens/sec · fine‑tuned on electrical failure datasets · zero‑shot reasoning for unknown fault signatures.
Live interactive demo on Hugging Face Spaces – feed sensor data and watch the AI detect & classify faults instantly.
Launch Hugging Face Appclick to play (simulated)