IOT-BASED AUTOMATIC WATERING SYSTEM FOR TOMATO PLANTS WITH SOIL MONITORING

Authors

  • Devanda Yudha Bharagus Universitas Negeri Surabaya
  • I Kadek Dwi Nuryana Universitas Negeri Surabaya

DOI:

https://doi.org/10.26740/jeisbi.v7i2.76210

Keywords:

Internet of Things (IoT), Arduino ESP32, Automatic Irrigation, Soil Moisture Sensor, Soil pH Sensor, Tomato Plants, Web Monitoring

Abstract

The development of the Internet of Things (IoT) technology has significantly contributed to plant maintenance, particularly in automated irrigation systems. Tomato plants require optimal soil conditions, especially soil moisture and soil pH, to grow properly. The ideal soil pH for tomato plants ranges from 6.0 to 6.8, while soil moisture levels should be maintained between 60% and 80%. However, manual tomato plant care often encounters problems due to a lack of understanding of plant requirements and improper irrigation timing. This study aims to design and develop an automatic tomato irrigation system based on the Internet of Things (IoT) with real-time monitoring of soil moisture and soil pH through a web-based interface. The system uses an ESP32 microcontroller as the main controller, along with a soil moisture sensor and a soil pH sensor. Sensor data are processed to automatically control the water pump based on a predetermined soil moisture threshold. System testing was conducted ten times under various soil conditions. The results show that when the soil moisture value exceeds 80%, the water pump automatically turns off, whereas when the value falls below 80%, the pump turns on to perform irrigation. These results indicate that the system operates according to the defined threshold and is able to maintain optimal soil moisture conditions. The implementation of this system improves the efficiency, effectiveness, and control of tomato plant maintenance.

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Published

2026-04-28

How to Cite

Bharagus, D. Y., & Nuryana, I. K. D. (2026). IOT-BASED AUTOMATIC WATERING SYSTEM FOR TOMATO PLANTS WITH SOIL MONITORING. Journal of Emerging Information Systems and Business Intelligence (JEISBI), 7(2), 227–236. https://doi.org/10.26740/jeisbi.v7i2.76210
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