Development and Evaluation of Solar Radiation Sensor Using Cost-Effective Light Sensors and Machine Learning Techniques
Furkejuvvon:
| Publikašuvnnas: | Technologies vol. 13, no. 5 (2025), p. 182 |
|---|---|
| Váldodahkki: | |
| Eará dahkkit: | , , , , , , , |
| Almmustuhtton: |
MDPI AG
|
| Fáttát: | |
| Liŋkkat: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| Fáddágilkorat: |
Eai fáddágilkorat, Lasit vuosttaš fáddágilkora!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3212132144 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2227-7080 | ||
| 024 | 7 | |a 10.3390/technologies13050182 |2 doi | |
| 035 | |a 3212132144 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231637 |2 nlm | ||
| 100 | 1 | |a Nava-Pintor, Jesús Antonio |u Posgrado en Ingeniería y Tecnología Aplicada, Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas 98000, Zacatecas, Mexico; jesus.nava@uaz.edu.mx (J.A.N.-P.); 37188129@uaz.edu.mx (U.E.A.-R.); hectorguerreroo@uaz.edu.mx (H.A.G.-O.); fabian.garcia@uaz.edu.mx (F.G.-V.); lsolis@uaz.edu.mx (L.O.S.-S.) | |
| 245 | 1 | |a Development and Evaluation of Solar Radiation Sensor Using Cost-Effective Light Sensors and Machine Learning Techniques | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The accurate measurement of solar radiation is essential for applications in agriculture, renewable energy, and environmental monitoring. Traditional pyranometers provide high-precision readings but are often costly and inaccessible for large-scale deployment. This study explores the feasibility of using low-cost ambient light sensors combined with statistical and machine learning models based on linear, random forest, and support vector regressions to estimate solar irradiance. To achieve this, an Internet of Things-based system was developed, integrating the light sensors with cloud storage and processing capabilities. A dedicated solar radiation sensor (Davis 6450) served as a reference, and results were validated against meteorological API data. Experimental validation demonstrated a strong correlation between sensor-measured illuminance and solar irradiance using the random forest model, achieving a coefficient of determination (R2) of 0.9922, a root mean squared error (RMSE) of 44.46 W/m2, and a mean absolute error (MAE) of 27.12 W/m2. These results suggest that low-cost light sensors, when combined with data-driven models, offer a viable and scalable solution for solar radiation monitoring, particularly in resource-limited regions. | |
| 653 | |a Accuracy | ||
| 653 | |a Humidity | ||
| 653 | |a Deep learning | ||
| 653 | |a Agricultural production | ||
| 653 | |a Internet of Things | ||
| 653 | |a Forecasting | ||
| 653 | |a Environmental monitoring | ||
| 653 | |a Productivity | ||
| 653 | |a Machine learning | ||
| 653 | |a Performance evaluation | ||
| 653 | |a Irradiance | ||
| 653 | |a Radiation | ||
| 653 | |a Radiation detectors | ||
| 653 | |a Efficiency | ||
| 653 | |a Feasibility studies | ||
| 653 | |a Agriculture | ||
| 653 | |a Embedded systems | ||
| 653 | |a Low cost | ||
| 653 | |a Pyranometers | ||
| 653 | |a Solar energy | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Environmental conditions | ||
| 653 | |a Root-mean-square errors | ||
| 653 | |a Neural networks | ||
| 653 | |a Sensors | ||
| 653 | |a Illuminance | ||
| 653 | |a Alternative energy sources | ||
| 653 | |a Light | ||
| 653 | |a Radiation measurement | ||
| 653 | |a Solar radiation | ||
| 700 | 1 | |a Alcalá-Rodríguez, Uriel E |u Posgrado en Ingeniería y Tecnología Aplicada, Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas 98000, Zacatecas, Mexico; jesus.nava@uaz.edu.mx (J.A.N.-P.); 37188129@uaz.edu.mx (U.E.A.-R.); hectorguerreroo@uaz.edu.mx (H.A.G.-O.); fabian.garcia@uaz.edu.mx (F.G.-V.); lsolis@uaz.edu.mx (L.O.S.-S.) | |
| 700 | 1 | |a Guerrero-Osuna, Héctor A |u Posgrado en Ingeniería y Tecnología Aplicada, Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas 98000, Zacatecas, Mexico; jesus.nava@uaz.edu.mx (J.A.N.-P.); 37188129@uaz.edu.mx (U.E.A.-R.); hectorguerreroo@uaz.edu.mx (H.A.G.-O.); fabian.garcia@uaz.edu.mx (F.G.-V.); lsolis@uaz.edu.mx (L.O.S.-S.) | |
| 700 | 1 | |a Mata-Romero, Marcela E |u Subdirección de Investigación, Centro de Enseñanza Técnica Industrial, C. Nueva Escocia 1885, Guadalajara 44638, Jalisco, Mexico; mmata@ceti.mx | |
| 700 | 1 | |a Lopez-Neri, Emmanuel |u Centro de Investigación, Innovación y Desarrollo Tecnológico CIIDETEC-UVM, Universidad del Valle de México, Tlaquepaque 45601, Jalisco, Mexico; emmanuel.lopezn@laureate.mx | |
| 700 | 1 | |a García-Vázquez Fabián |u Posgrado en Ingeniería y Tecnología Aplicada, Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas 98000, Zacatecas, Mexico; jesus.nava@uaz.edu.mx (J.A.N.-P.); 37188129@uaz.edu.mx (U.E.A.-R.); hectorguerreroo@uaz.edu.mx (H.A.G.-O.); fabian.garcia@uaz.edu.mx (F.G.-V.); lsolis@uaz.edu.mx (L.O.S.-S.) | |
| 700 | 1 | |a Solís-Sánchez, Luis Octavio |u Posgrado en Ingeniería y Tecnología Aplicada, Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas 98000, Zacatecas, Mexico; jesus.nava@uaz.edu.mx (J.A.N.-P.); 37188129@uaz.edu.mx (U.E.A.-R.); hectorguerreroo@uaz.edu.mx (H.A.G.-O.); fabian.garcia@uaz.edu.mx (F.G.-V.); lsolis@uaz.edu.mx (L.O.S.-S.) | |
| 700 | 1 | |a Carrasco-Navarro, Rocío |u Department of Mathematics and Physics, ITESO, Tlaquepaque 45604, Jalisco, Mexico; rociocarrasco@iteso.mx | |
| 700 | 1 | |a Luque-Vega, Luis F |u Department of Technological and Industrial Processes, ITESO, Tlaquepaque 45604, Jalisco, Mexico | |
| 773 | 0 | |t Technologies |g vol. 13, no. 5 (2025), p. 182 | |
| 786 | 0 | |d ProQuest |t Materials Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3212132144/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3212132144/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3212132144/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |