ROVIGA: Model-Driven Soil Moisture Sensor for Internet-Connected Plant Pot
Abstract
The soil moisture sensor provides numerical measurements to detect changes in soil moisture using an analog voltage output. This research aims to develop a capacitive sensor based on a statistical model to detect soil moisture for plant watering, leveraging the Internet of Things (IoT). The analysis was conducted using polynomial and linear regression models. The modeling process was based on primary gravimetric test results from dried soil. The best model coefficients, selected based on the highest adjusted R-squared value, were used for sensor recalibration. A watering system was then developed using an Arduino and a model-driven capacitive soil moisture sensor integrated into an internet-connected smart plant pot, enabling remote control via a mobile phone. The research findings indicate that the 8th-order polynomial model, with the highest adjusted R-squared value of 0.9583, is the most accurate. The smart watering system using the model-driven capacitive sensor achieved soil moisture prediction outcomes ranging from 0.08 to 1.01 for 150 to 418 sensor data points. The internet-connected smart plant pot allows precise and real-time control, delivering notifications and enabling actions when plants require watering.
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References
R. S. Ferrarezi, T. A. R. Nogueira, and S. G. C. Zepeda, “Performance of soil moisture sensors in Florida Sandy Soils,” Water (Switzerland), vol. 12, no. 2, pp. 1–20, 2020, doi: 10.3390/w12020358.
C. M. Firma, A. A. Pramudita, and D. Arseno, “Pemodelan Estimasi Kandungan Air Pada Tanah Berbasis Ground Penetrating Radar (gpr) Dengan Vector Network Analyzer,” eProceedings Eng., vol. 8, no. 6, Dec. 2021, Accessed: May 18, 2024. [Online]. Available: https://openlibrarypublications.telkomuniversity.ac.id/index.php/engineering/article/view/17158
Z. Mohune, L. Burhan, and B. Sjahril, “Sistem Kontrol Penyiram Bunga Pada Pot Menggunakan Smart Rellay Pada Bangunan Rumah Bertingkat,” J. Teknol. Pertan. Gorontalo, vol. 2, no. 2, 2017, [Online]. Available: http://jurnal.poligon.ac.id/index.php/jtpg/article/download/122/66
E. A. A. D. Nagahage, I. S. P. Nagahage, and T. Fujino, “Calibration and validation of a low-cost capacitive moisture sensor to integrate the automated soil moisture monitoring system,” Agric., vol. 9, no. 7, Jul. 2019, doi: 10.3390/AGRICULTURE9070141.
G. S. Campbell et al., “Method A: Soil-Specific Calibrations For Meter Soil Moisture Sensors,” metergroup, 2023. http://publications.metergroup.com/Sales and Support/METER Environment/Website Articles/Method_a_soil_specific_calibrations_for_meter_soil_moisture_sensors.pdf (accessed Aug. 22, 2023).
A. E. Putra and D. A. Juarna, “Prediksi Produksi Daging Sapi Nasional dengan Metode Regresi Linier dan Regresi Polinomial,” J. Ilm. Komputasi, vol. 20, no. 2, pp. 209–216, 2021, doi: 10.32409/jikstik.20.2.2722.
I. Setiawan, J. Junaidi, F. Fadjryani, and F. R. Amaliah, “Automatic Plant Watering System for Local Red Onion Palu using Arduino,” J. Online Inform., vol. 7, no. 1, pp. 28–37, Jun. 2022, doi: 10.15575/JOIN.V7I1.813.
I. Setiawan, Junaidi, Fadjryani, and F. R. Amaliah, Mobile App for Plant Watering System with Verticulture Planting Technique. Atlantis Press International BV, 2023. doi: 10.2991/978-94-6463-228-6.
I. Setiawan, M. D. T. Musa, and S. A. Putri, “Re-Calibration of Model-Based Capacitive Sensor for IoT Soil Moisture Measurements,” J. Appl. Informatics Comput., vol. 7, no. 2, pp. 150–155, 2023, doi: 10.30871/jaic.v7i2.6809.
R Core Team, “R: A Language and Environment for Statistical Computing.” Vienna, Austria, 2023. [Online]. Available: https://www.r-project.org/
W. Chang et al., “shiny: Web Application Framework for R.” 2022. [Online]. Available: https://shiny.rstudio.com/
A. I. Satrio and D. H. R. Saputra, “Design and Build IoT-Based Lavender Plant Smart Pots,” Indones. J. Innov. Stud., vol. 13, p. 10.21070/ijins.v13i.530, Jan. 2021, doi: 10.21070/ijins.v13i.530.
“Blynk: a low-code IoT software platform for businesses and developers.” https://blynk.io/ (accessed Aug. 10, 2024).
M. Fezari and A. Al Dahoud, “(PDF) Integrated Development Environment ‘IDE’ For Arduino,” 2018. https://www.researchgate.net/publication/328615543_Integrated_Development_Environment_IDE_For_Arduino (accessed Aug. 10, 2024).
A. Shukla et al., “Soil Moisture Estimation using Gravimetric Technique and FDR Probe Technique : A Comparative Analysis,” no. January, pp. 89–92, 2014.
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