Industrial IoT Monitoring

Industrial IoT monitoring system combining OPC UA simulation, LSTM autoencoder anomaly detection, and local LLM explanations for real-time equipment monitoring with natural language insights.

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.