Development of a low-cost pyranometer using a Light-Dependent Resistor (LDR)

Authors

Keywords:

Regression modeling, Solar energy, Low-cost Pyranometer, Microcontroller

Abstract

A pyranometer is an essential device used to measure the intensity of solar radiation. It has a wide range of applications, including meteorology, energy, building systems, and agriculture. However, the high cost of this equipment is a major barrier to its use. This research aims to develop a low-cost pyranometer by using a Light-Dependent Resistor (LDR). Three LDRs were connected in series with a resistor of 100, 500, and 1,000 ohms. The voltage data was collected using an Arduino Mega 2560 microcontroller board. The results were then compared with a KIPP & ZONEN CMP3 pyranometer, which served as the reference device. A total of 4,296 data points were collected. The data was analyzed using Multiple Linear Regression to create and test a regression equation. The results showed that the equation between the voltage of 100, 500, and 1,000 ohm resistors and the natural logarithm of the solar radiation intensity on a day with a maximum, minimum, and average light intensity of 1,131.5, 123.5, and 672 watts per square meter, respectively, has an R2 value of 0.979 and RMSEP of 54.913. This error was relatively small, indicating that the developed device can be a useful tool.

References

ACDC Shop. (2025). LDR sensor datasheet. ACDC Shop. https://www.acdcshop.gr/content/02-LDR1.pdf

Avallone, E., Mioralli, P. C., Scalon, V. L., Padilha, A., & Oliveira, S. D. R. (2018). Thermal pyranometer using the open hardware Arduino platform. International Journal of Thermodynamics, 21(1), 1–5. https://doi.org/10.5541/ijot.5000209000

Bruce, P., & Bruce, A. (2017). Practical statistics for data scientists. O’Reilly Media.

Chaioek, R., Chookakorn, P., & Chanthophas, W. (2017). Variable selection methods in multiple linear regression analysis [Paper presentation]. In Seminar on Applied Statistics for Solving Economic and Social Problems. Khon Kaen University. (In Thai)

Chen, W. H., Mattson, N. S., & You, F. (2022). Intelligent control and energy optimization in controlled environment agriculture via nonlinear model predictive control of semi-closed greenhouse. Applied Energy, 320, 119334. https://doi.org/10.1016/j.apenergy.2022.119334

de Barros, R. C., Callegari, J. M. S., do Carmo Mendonça, D., Amorim, W. C. S., Silva, M. P., & Pereira, H. A. (2018). Low-cost solar irradiance meter using LDR sensors. In 2018 13th IEEE International Conference on Industry Applications (INDUSCON) (pp. 72-79). IEEE.

International Organization for Standardization. (2018). ISO 9060:2018: Solar energy-Specification and classification of instruments for measuring hemispherical solar and direct solar radiation. ISO. https://www.iso.org/obp/ui/#iso:std:iso:9060:en

Khajornsak, S. (2019). Reduction of heat from solar energy for misting greenhouse [Master’s thesis]. Suranaree University of Technology. http://sutir.sut.ac.th:8080/jspui/handle/123456789/8744. (In Thai)

Kipp & Zonen. (2025). Datasheet CMP3 & SMP3 pyranometers. Kipp & Zonen. https://www.kippzonen.com/Download/1067/Datasheet-CMP3-SMP3-pyranometers-EN

Linani, M., Mokhtari, B., & Cheknane, A. (2021). Design of low-cost pyranometer sensors based on artificial neural network for an electric vehicle. In 2021 3rd International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA) (pp. 990–994). IEEE. https://doi.org/10.1109/SUMMA53307.2021.9632031

Moreno-Garcia, I. M., Palacios-García, E. J., Santiago, I., Pallares-López, V., & Moreno-Munoz, A. (2016). Performance monitoring of a solar photovoltaic power plant using an advanced real-time system. In 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC) (pp. 1–6). IEEE. https://doi.org/10.1109/EEEIC.2016.7555473

Osinowo, M. O., Willoughby, A. A., Ewetumo, T., & Kolawole, L. B. (2019). Development of a low-cost pyrometer using locally sourced materials. International Journal for Scientific Research & Development, 7(5), 133-136.

Pansanato, C., Gonçalves, G. B., Ito, M. C., Scalon, V. L., Avallone, E., & Garcia, R. P. (2018). Low-cost thermal pyranometer using Dallas DS18B20 sensor and Arduino. In 17th Brazilian Congress of Thermal Sciences and Engineering (ENCIT 2018). ABCM. https://abcm.org.br/proceedings/view/CIT18/0603

Ronilaya, F., Ramadhani, P. F., Hidayat, M. N., Wibowo, S., Eryk, I. H., & Pratama, S. S. V. P. (2022). A development of a low-cost solar irradiance meter using mini solar cells. In 2022 International Conference on Informatics, Electrical and Electronics (ICIEE). IEEE. https://doi.org/10.1109/ICIEE55596.2022.10010326

Published

2026-08-27

How to Cite

Waksang, N., Treeamnuk, T., Treeamnuk, K., & Thingborirak, W. (2026). Development of a low-cost pyranometer using a Light-Dependent Resistor (LDR). Agriculture & Technology RMUTI Journal, 7(2), 61–70. retrieved from https://li01.tci-thaijo.org/index.php/atj/article/view/268823