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IoT-Based Drip System Using NodeMCU Module and Arduino UNO for Hydroponics

Authors

Raphael Gabriel T. Dineros

Cor Jesu College, Inc., Philippines (PH)

Francis Elijah L. Cago

Cor Jesu College, Inc., Philippines (PH)

Cleford Jay D. Bacan

Cor Jesu College, Inc., Philippines (PH)

Zeth Andrade E. Canales

Cor Jesu College, Inc., Philippines (PH)

Rolando S. Carvajal III

Cor Jesu College, Inc., Philippines (PH)

Mark Jobert C. Ellaga

Cor Jesu College, Inc., Philippines (PH)

Arn Crissin N. Garciano

Cor Jesu College, Inc., Philippines (PH)

Bryan G. Maravillas

Cor Jesu College, Inc., Philippines (PH)

Jan Froimhel U. Matab

Cor Jesu College, Inc., Philippines (PH)

Nathaniel B. Tahil

Cor Jesu College, Inc., Philippines (PH)

Vince Anthony O. Tamesis

Cor Jesu College, Inc., Philippines (PH)

Article Information

DOI: 10.51583/IJLTEMAS.2025.140500040

Subject Category: Engineering

Volume/Issue: 14/5 | Page No: 397-405

Publication Timeline

Submitted: 2025-06-09

Published: 2025-06-09

Abstract

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.

Keywords

hydroponic farming, Arduino UNO, NodeMCU module, Philippines,, quantitative research

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