Author: Wajid Hussain
Master’s Project in Cyber-Physical Systems
Advisors: Dr. Rolando Herrero, Dr. Haitham Tayyar
This project aims to enhance solar panel efficiency by developing an Intelligent Solar Panel Orientation System using ESP32-CAM, LoRa communication, and IoT-based data processing. By integrating image analysis, sun-tracking algorithms, and long-range communication, the system dynamically adjusts solar panel orientation for optimal energy efficiency.
- ESP32-CAM: Captures images using Wi-Fi to detect the sun's position.
- LoRa Modules: Facilitate long-range communication between the ESP32 and a laptop.
- Solar Tracking Mechanism: Adjusts the panel orientation based on sun position data.
- Sun Position Calculation: Uses libraries like Skyfield, Ephem, PySolar, and PVlib for accurate sun positioning.
- LoRa Communication: Sends activation commands from the laptop to the ESP32 to adjust the solar panel.
- Cloud Integration: Sends data via MQTT for real-time monitoring and visualization.
- Image Capture: ESP32-CAM captures images over Wi-Fi every 30 minutes.
- Image Processing: The laptop verifies the sun's position.
- LoRa Transmission: Activation commands are sent to the ESP32 to adjust the panel.
- Cloud Monitoring: Data is sent to a cloud platform for real-time updates.
This project integrates IoT, image processing, and sun-tracking algorithms to create an intelligent solar panel system. The system offers real-time optimization and remote monitoring, providing a scalable solution for renewable energy applications.
- ESP32-CAM Setup: Configure with Wi-Fi for image capture.
- LoRa Setup: Enable communication between ESP32 and laptop.
- Laptop: Process image data and calculate sun position.
- Solar Tracking: Adjust panel orientation based on sun data.
- Power the ESP32-CAM and LoRa modules.
- Use the laptop to monitor and control the system.