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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62189
Volume:
10 |
4 |
April 2026
Pages:
1-7
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Science & Engineering
Anjuman College of Engineering & Technology, Nagpur, Maharashtra, India
Department of Computer Science & Engineering
Anjuman College of Engineering & Technology, Nagpur, Maharashtra, India
Department of Computer Science & Engineering
Anjuman College of Engineering & Technology, Nagpur, Maharashtra, India
Department of Computer Science & Engineering
Anjuman College of Engineering & Technology, Nagpur, Maharashtra, India
Department of Computer Science & Engineering
Anjuman College of Engineering & Technology, Nagpur, Maharashtra, India
Department of Computer Science & Engineering
Anjuman College of Engineering & Technology, Nagpur, Maharashtra, India
The increasing demand for sustainable energy solutions has accelerated the adoption of solar photovoltaic systems. However, conventional fixed solar panels suffer from reduced efficiency due to their inability to maintain optimal alignment with the sun. This research presents an IoT-based dual-axis solar tracking system designed to maximize energy harvesting by continuously adjusting the panel orientation based on sunlight intensity. The system utilizes LDR sensors for detecting solar position, an ESP32 microcontroller for processing, and servo motors for actuation. Additionally, environmental parameters such as temperature and humidity are monitored using a DHT11 sensor and transmitted to a cloud platform for real-time visualization. Experimental results demonstrate a significant improvement in energy output compared to fixed-panel systems. The proposed solution is cost-effective, scalable, and suitable for residential and industrial applications.
KEYWORDS
The proposed IoT-based dual-axis solar tracking system successfully improves the efficiency of solar energy generation by continuously aligning the panel with the direction of maximum sunlight. Unlike fixed solar panels, the system dynamically adjusts its position, resulting in a significant increase in energy output. The integration of LDR sensors, ESP32 microcontroller, and servo motors ensures accurate tracking, while the DHT11 sensor provides useful environmental data. The addition of IoT functionality enables real-time monitoring and remote access through a cloud platform, making the system more user-friendly and efficient. The experimental results indicate that the system achieves a noticeable improvement in energy generation, especially under clear weather conditions. Overall, the system is cost-effective, reliable, and suitable for practical applications in various fields.
1] Buswig, Y. et al. (2026). Dual-axis solar tracking system with IoT monitoring using Arduino MEGA and Cayenne platform. International Journal of Renewable Energy Research, 16(1), 45–54. [2] Achbi, M. (2024). Industrial dual-axis solar tracking system with SCADA-based web monitoring. Journal of Energy Systems, 8(3), 112–125. [3] Vinodhkumar, V., & John, A. (2020). Astronomical dual-axis solar tracking system using GPS and RTC modules. Proceedings of the International Conference on Renewable Energy Technologies (ICRET), IEEE, pp. 88–93. [4] Al-Sheikh, H. (2025). Validation of ESP32 and Blynk platform for IoT-based solar tracking applications. International Journal of Electronics and Communication Engineering, 12(4), 201–210. [5] Maharani, R. (2025). IoT-based dual-axis solar tracking with DHT11 environmental monitoring using ESP32 and Blynk. Journal of Emerging Technologies in Engineering Applications, 4(2), 88–97. [6] Atienza, J. R., et al. (2024). Single-axis IoT solar tracking system using Arduino Uno and Blynk: Design and performance evaluation. International Journal of Advanced Engineering and Technology, 7(1), 33–41. [7] Katyal, R., Sharma, P., & Gupta, A. (2022). Machine learning-enhanced dual-axis solar tracking with ThingSpeak IoT integration. Proceedings of the IEEE International Conference on Smart Energy Systems, pp. 334–341. [8] Rahaim, M. et al. (2023). Educational IoT dual-axis solar tracker using Arduino and Blynk. International Journal of Electrical Engineering and Sustainability, 5(1), 56–64. [9] Esposito, A., & Antonini, A. (2022). Photovoltaic systems with solar tracking: A review of technologies and performance. Renewable and Sustainable Energy Reviews, 152, 111712. [10] Seme, S., Srpčič, G., & Sredenšek, K. (2020). Analysis of dual-axis solar tracking systems: A comprehensive review. Energy Reports, 6(2), 175–189.
Publication Date
5/1/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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