Inspiration

Solar power plants can lose performance because of hotspots, dust, environmental changes, and other panel abnormalities. Manual inspection of large solar installations is time-consuming and difficult to scale.

We wanted to create a centralized platform that combines solar performance monitoring with thermal inspection and AI-assisted fault detection.

What it does

SolarPulse AI is an AI-assisted solar monitoring platform that combines electrical and environmental telemetry with thermal inspection.

The dashboard provides:

Real-time solar voltage, current and power monitoring
Irradiance and environmental monitoring
Power and efficiency analytics
Thermal hotspot inspection
AI-assisted fault classification
Risk-based alerts
Maintenance prioritization

How we built it

The current prototype was developed as a web-based industrial IoT dashboard using HTML, CSS and JavaScript, with Chart.js for analytics.

The proposed hardware architecture uses INA226 for electrical measurements, an irradiance sensor and BME280 for environmental data, MLX90640 for thermal inspection, ESP32 for edge data collection, and Raspberry Pi for thermal image processing and AI inference.

The prototype currently demonstrates the complete workflow using simulated telemetry and a representative thermal image. Physical sensor integration and trained CNN inference are planned for the next stage.