AI Meets Solar: Smart Dual-Axis Tracking for Sustainable Energy and Social Well-being

Abstract

The rising global demand for clean and renewable energy necessitates innovations that improve solar photovoltaic (PV) system efficiency. This study presents the development of AI Meets Solar, a smart dual-axis solar tracker integrating artificial intelligence and fuzzy logic control to optimize panel orientation in real time. The system employs an ESP32 microcontroller, four Light Dependent Resistors (LDRs) in a quadrant configuration, and two high-torque servo motors to continuously align the panel with the sun’s position. AI algorithms enable adaptive decision-making, enhancing responsiveness to changing weather and light conditions. Experimental results show a 14% efficiency improvement compared to fixed systems, demonstrating the effectiveness of combining mechanical motion with intelligent control. Beyond technical gains, the research aligns with Islamic principles of environmental stewardship (ḥifẓ al-bi’ah) and public benefit (maṣlaḥah), contributing to sustainable energy use and social well-being. The findings highlight the potential of AI-powered solar tracking as both a technological innovation and an ethical approach to addressing future energy challenges.