ADAPTIVE WATERING SYSTEM BASED INTERNET OF THINGS FOR EVALUATING ACTUAL WATER VOLUME IN CURLY TOMATOES

Saipullah; Abdul Latief Arda; Imran Taufiq; Andani Achmad; Supriadi Sahibu; Abdul jalil

doi:10.63922/ijebir.v5i04.4846

Saipullah Sistem komputer, Universitas Handayani Makassar
Abdul Latief Arda Sistem komputer, Universitas Handayani Makassar
Imran Taufiq Sistem komputer, Universitas Handayani Makassar
Andani Achmad Teknik Elektro, Universitas Hasanuddin
Supriadi Sahibu Sistem komputer, Universitas Handayani Makassar
Abdul jalil Teknik Informatika dan Komputer, Politeknik Negeri Ujung Pandang

DOI: https://doi.org/10.63922/ijebir.v5i04.4846

Keywords: Internet of Things; adaptive irrigation; multimodal sensor; soil moisture; flow sensor; actual water volume

Abstract

Irrigation management for curly tomato plants (Solanum lycopersicum L.) grown in polybags requires controlled water application because the limited growing medium may cause rapid soil moisture changes. This study developed an Internet of Things-based adaptive irrigation system with multimodal sensors to evaluate actual water volume. The system integrates an ESP32 microcontroller, soil moisture sensor, DHT22, light intensity sensor, flow sensor, relay, water pump, LCD, and Android-based monitoring application. Irrigation decisions are determined based on soil moisture, irrigation schedule, temperature condition, and daily water target. The system was tested for 21 days with three observations per day, resulting in 63 observations. Evaluation was conducted using sensor data analysis, confusion matrix, actual water volume measurement, and comparison with a fixed duration method. The results showed 14 True Positive, 45 True Negative, 1 False Positive, and 3 False Negative decisions, resulting in 93.65% decision accuracy. The flow sensor recorded a total water volume of 6.539 L per polybag during the 21-day test. Compared with the fixed duration method of 16.800 L per polybag, the adaptive system produced 61.08% lower irrigation volume. These results indicate that the proposed system can operate selectively and support more measurable water management.

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