A complete industrial IoT stack that combines real-time anomaly detection with AI-powered explanations for manufacturing equipment monitoring. Integrates an OPC UA simulator generating realistic production machine data, an LSTM autoencoder for anomaly scoring, and a local LLM (llama.cpp) providing natural language explanations of detected issues through database-backed MCP tools. Includes Bayesian optimization for automated setpoint tuning, WebIQ HMI integration, and supports both CPU and GPU inference with automatic hardware detection.
Cognium trust score
50%
Tier
Unverified
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.
Returns 7 tools: search_skills, get_skill, list_leaderboard, get_trust_breakdown, resolve_composition, plus the ChatGPT-connector search and fetch. Every tool is annotated read-only.
Resolve this skill directly via MCP tools/call get_skill.