Alif et al. (2025) Design and Implementation of an IoT-Based Smart Drip Irrigation System Using Takagi-Sugeno Fuzzy Logic for Melon Cultivation

Identification

• Journal: Journal of Applied Informatics and Computing
• Year: 2025
• Date: 2025-12-08
• Authors: M Nurfadli Alif, Kharisma Monika Dian Pertiwi
• DOI: 10.30871/jaic.v9i6.11424

Research Groups

• Universitas Telkom

Short Summary

This study designed and implemented an Internet of Things (IoT)-based smart drip irrigation system using Takagi-Sugeno fuzzy logic to precisely regulate water supply for melon cultivation in a greenhouse. The system successfully maintained soil moisture within the optimal range of 60%–80%, though plant growth evaluation indicated limitations in promoting overall healthy development, suggesting the need for further refinement considering additional environmental factors.

Objective

• To design and implement an IoT-based smart drip irrigation system utilizing Takagi-Sugeno fuzzy logic to optimize water supply for melon (Cucumis melo L.) cultivation in a greenhouse environment.

Study Configuration

• Spatial Scale: Mini greenhouse containing two melon plants.
• Temporal Scale: 10-day experimental testing period for sensor performance, solenoid valve accuracy, system reliability, and plant growth evaluation.

Methodology and Data

• Models used: Takagi-Sugeno fuzzy logic (zero-order model) for irrigation control, designed and simulated using MATLAB, and implemented on an ESP8266 microcontroller using Arduino IDE.
• Data sources:
  • Capacitive soil moisture sensor (YL-69)
  • DS18B20 temperature sensor
  • ESP8266 microcontroller for data processing and control
  • Firebase Realtime Database (cloud platform) for real-time data storage and synchronization
  • Web-based interface for monitoring and visualization

Main Results

• The system effectively maintained soil moisture within the optimal range of 60%–80%, with an average of 64.53% during the 10-day test.
• Ambient temperature averaged 31.48 °C, which was slightly higher than the ideal range of 25–30 °C for melon growth.
• The solenoid valve's real-world performance showed an average error of 1.18% compared to MATLAB simulations, demonstrating precise control.
• The IoT system exhibited a sensor-to-dashboard latency of approximately 2–3 seconds and high reliability, with 97.8% uptime and 98.5% data transmission success.
• While the fuzzy-IoT system maintained stable soil moisture and promoted more leaves, manual irrigation resulted in slightly greater plant height (14 cm vs 13 cm) and leaf width (8 cm vs 7.5 cm), indicating that other factors like ambient temperature, humidity, and nutrient availability were not fully optimized by the current system.

Contributions

• Development of a specific IoT-based smart drip irrigation system tailored for melon cultivation in a greenhouse, addressing the lack of crop-specific solutions in existing literature.
• Implementation of a tuned Takagi-Sugeno fuzzy logic model with discrete singleton outputs (0, 240, 480, 720 seconds) for efficient execution on a microcontroller.
• Integration with Firebase Realtime Database, providing real-time monitoring with user authentication, and detailed reporting of end-to-end latency and reliability metrics.
• Empirical comparison of plant growth between the fuzzy-IoT automated system and manual irrigation, highlighting the system's strengths in soil moisture stability and identifying areas for improvement in holistic plant development.

Funding

Not specified in the provided text.

Citation

@article{Alif2025Design,
  author = {Alif, M Nurfadli and Pertiwi, Kharisma Monika Dian},
  title = {Design and Implementation of an IoT-Based Smart Drip Irrigation System Using Takagi-Sugeno Fuzzy Logic for Melon Cultivation},
  journal = {Journal of Applied Informatics and Computing},
  year = {2025},
  doi = {10.30871/jaic.v9i6.11424},
  url = {https://doi.org/10.30871/jaic.v9i6.11424}
}