<![CDATA[The global energy crisis is a complex phenomenon involving an imbalance between increasingly limited energy supplies and ever-rising demand, driven by geopolitical dynamics, shifts in the energy market, and the challenges of transitioning to renewable energy sources. In a country as vast as Indonesia, the potential for developing renewable energy such as solar, hydro, wind, and geothermal energy is significant. This potential presents an opportunity for Indonesia’s resilience in the national energy sector. Utilizing solar energy through solar panels requires an optimized system to maximize the generated electrical power. This research aims to design an IoT-integrated single-axis solar tracking system using an ESP32 microcontroller to enhance the capacity of solar panels. The research methodology includes designing an algorithm to control the rotation angle of the solar tracker using an LDR sensor to determine the intensity of the sun’s electromagnetic waves and to drive the servo motor so that the panel is perpendicular to the sunlight. Solar panel temperature monitoring is performed using a MAX6675 sensor. For real-time current and voltage measurements, an INA219 sensor is used. The results of the solar panel data, processed adaptively by a control algorithm based on sensor data, are displayed on the LCD screen and transmitted to the Blynk IoT platform. The research findings indicate that the maximum power capacity recorded on the Blynk monitoring app was 1.75 watts at 12:00 PM, when solar intensity was at its peak. After 12:00 PM, power generation began to decline in tandem with the decrease in sunlight intensity in the afternoon. The data on power generation from this single-axis solar tracking system indicates that the use of this algorithm is capable of increasing the power absorbed by the solar panels and optimizing the use of solar energy.]]>
