Predictive Maintenance Monitor for smart appliances. ApplianceIQ uses physical hardware sensors and real-time data streaming to detect mechanical wear and prevent catastrophic appliance failure.

• Real-Time Telemetry: Instantaneous readings of your appliance's electrical draw.
• Predictive Health Scoring: Dynamically scales machine health based on live current limits.
• Harmful Limit Detection: Immediately triggers an emergency browser alert if an appliance is blocked or drawing dangerous levels of current.
• AI Storytelling Synthesis: Translates raw sensor data into plain-English "chapter updates" via Manus AI, making machine health relatable and actionable.

Hardware & Firmware

• ESP32 Microcontroller: Acts as the edge-processing brain, capturing high-frequency analog readings from the current sensor.
• Analog Current Sensor: Measures raw motor load and physical resistance in real-time.
• C++ / Arduino (PlatformIO): Custom firmware written in C++ that processes Raw ADC values, calculates the True RMS current, and runs the baseline boundary logic at the edge.

Backend & Real-Time Data Pipeline

• Node.js: Powers the lightweight bridge (bridge.js) that reads serial data coming from the ESP32.
• MQTT (HiveMQ): Acts as the ultra-low latency messaging broker, streaming the JSON telemetry from the backend bridge directly to the frontend clients.

Frontend & Interactive Dashboard

• React & Vite: Drives the fast, dynamic, and responsive web dashboard.
• Recharts: Used to build the live-updating, animated telemetry chart that plots the live current against our maximum risk baseline boundaries.
• Vanilla CSS: Custom-tailored CSS for a premium, highly engaging user interface with dynamic visual status indicators.
• Manus AI Integration: Synthesizes raw sensor telemetry into a human-readable narrative story, bridging the gap between raw data and understandable machine health!

1. Hardware: Flash the ESP32 firmware located in the current-sensor directory using PlatformIO.
2. Backend Bridge: Open a terminal in the dashboard folder and run node bridge.js to begin pushing USB serial data to MQTT.
3. Frontend Dashboard: Open another terminal in the dashboard folder, run npm install and then npm run dev to launch the React interface.