Enhanced Solar Tracking System Utilizing IoT for Optimal Energy

This research work presents a novel approach to solar tracking systems, leveraging Internet of Things (IoT) technology coupled with predictive analytics to dynamically optimize solar panel orientation for maximal energy yield. The proposed system integrates a network of IoT sensors to continuously monitor environmental parameters such as solar irradiance, temperature, humidity, wind speed, and cloud coverage. Real-time data processing and predictive algorithms enable the proposed solar tracking system to dynamically adjust solar panel angles, ensuring optimal alignment with the sun's position. The proposed system's cloud-connected architecture enables remote monitoring and control, offering users insights into system performance and the ability to override settings as needed. Experimental results demonstrate the effectiveness of the proposed solar tracking system in enhancing energy efficiency and adapting to changing environmental conditions.