Three Dimensional Solar Tracking Using Machine Learning

The primary goal is to gather the sun energy in the most effective way possible using this design, decreasing reliance on fossil fuels and drastically lowering the cost of power. In this project by using a three-dimensional solar tracking system that moves the solar panel to a stronger sunlight location. The movements of two fixed servo motors that rotates the solar panel in two axes were controlled by an ATmega328P microcontroller. The Machine learning algorithm known as KNN algorithm is employed here for the prediction of future power output. The DHT11 sensor is used for recording the temperature. The values recorded from the temperature sensor and current sensor is sent to the cloud platform through machine learning. The H-bridge controller Controls the servo motor based on the firing pulse provided by the ATmega238P based upon the light intensity. Servo motors can be used to move the solar panel along the X-axis as well as the Y-axis. The values are compared to one another using a certain LDR value as a benchmark. As a result, the solar panel output power is increased.