IoT-Based Drip System Using NodeMCU Module and Arduino UNO for Hydroponics
Raphael Gabriel T. Dineros,
Francis Elijah L. Cago,
Cleford Jay D. Bacan,
Zeth Andrade E. Canales,
Rolando S. Carvajal,
Mark Jobert C. Ellaga,
Arn Crissin N. Garciano,
Bryan G. Maravillas,
Jan Froimhel U. Matab,
Nathaniel B. Tahil and
Vince Anthony O. Tamesis
Additional contact information
Raphael Gabriel T. Dineros: Cor Jesu College, Inc., Philippines
Francis Elijah L. Cago: Cor Jesu College, Inc., Philippines
Cleford Jay D. Bacan: Cor Jesu College, Inc., Philippines
Zeth Andrade E. Canales: Cor Jesu College, Inc., Philippines
Rolando S. Carvajal: Cor Jesu College, Inc., Philippines
Mark Jobert C. Ellaga: Cor Jesu College, Inc., Philippines
Arn Crissin N. Garciano: Cor Jesu College, Inc., Philippines
Bryan G. Maravillas: Cor Jesu College, Inc., Philippines
Jan Froimhel U. Matab: Cor Jesu College, Inc., Philippines
Nathaniel B. Tahil: Cor Jesu College, Inc., Philippines
Vince Anthony O. Tamesis: Cor Jesu College, Inc., Philippines
International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 5, 397-405
Abstract:
Hydroponic farming is a widely used method that utilizes nutrient-rich water instead of soil to grow plants. Several studies showed that new technologies have been implemented in hydroponic farming, particularly to improve its irrigation system. Thus, this study incorporated the Node MCU and Arduino Uno module. The system will use the system hardware and the Blynk IoT application, in which real-time readings of the sensors will automatically be displayed on the LED display on the panel and the phone. This research used an experimental design. It utilized the descriptive-comparative design in interpreting the data to determine the differences in the average activation time between the system hardware and the Blynk IoT application. The system has been programmed using the Node MCU and Arduino Uno module, and sensors have been installed to determine the temperature and soil moisture in hydroponics. Four hundred trials have been conducted to test the different functions of hydroponics. The results indicate that in terms of the function in water and AI mode, utilizing Blynk IoT and system hardware vary significantly. The system activates at an average of 7.41 with a standard deviation of 1.40 seconds. The water mode and AI mode operations are at an average of .32 and 1.80 and have a standard deviation of 0.14 and 0.22 seconds, respectively. Furthermore, the p-value is 0.000, less than 0.05, rejecting the null hypothesis.
Date: 2025
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