Arvita Agus Kurniasari, Pramuditha Shinta Dewi Puspitasari, Lukie Perdanasari, Dia Bitari Mei Yuana, Jumiatun Jumiatun

An Intelligent Fuzzy Logic-Controlled IoT System for Efficient Hydroponic Plant Monitoring and Automation

Introduction

An intelligent fuzzy logic-controlled iot system for efficient hydroponic plant monitoring and automation. Optimize hydroponic farming with an Intelligent Fuzzy Logic-Controlled IoT System. Monitor temperature, pH, TDS & automate processes for efficient plant growth, resource control & sustainable agriculture.

Abstract

This paper addresses the challenges of optimizing environmental conditions in hydroponic farming by integrating an Intelligent Fuzzy Logic-Controlled IoT System. The research problem lies in the inefficiency of traditional hydroponic monitoring systems, particularly in maintaining ideal conditions for plant growth while minimizing resource waste. This study aims to develop a system that leverages IoT technology and fuzzy logic to monitor and automate hydroponic processes more efficiently. Using sensors, the system continuously tracks key environmental parameters such as temperature, humidity, soil moisture, pH levels, and total dissolved solids (TDS). A fuzzy logic controller (FLC) triggers actions based on predefined rules. During testing, the system showed effective performance—for example, activating fans when temperature (31.2°C) and humidity (60%) indicated a need for cooling, and adjusting nutrient levels when pH (5.8) and TDS (450 ppm) were suboptimal. The system offers practical benefits through real-time adaptation using defuzzification and aggregation, ensuring precise resource control, improving efficiency, and reducing waste. This study highlights the system's potential to support sustainable agriculture by providing scalable solutions that enhance plant growth and optimize resource use, especially for small-scale farmers and urban farming initiatives.

Review

This paper presents an intelligent IoT system integrating fuzzy logic control to address the critical challenges of optimizing environmental conditions and resource management in hydroponic farming. The core problem highlighted is the inefficiency of conventional monitoring systems in maintaining ideal plant growth environments and minimizing waste. By proposing a system that combines real-time data acquisition via IoT with the nuanced decision-making capabilities of fuzzy logic, the authors aim to significantly enhance the efficiency and automation of hydroponic processes, a crucial step towards more sustainable agricultural practices. The methodology details a sensor-driven framework that continuously tracks vital environmental parameters, including temperature, humidity, pH levels, and total dissolved solids (TDS). The novelty lies in the Fuzzy Logic Controller (FLC), which interprets these inputs through predefined rules to trigger adaptive actions. The abstract provides illustrative examples of the system's performance, such as its ability to activate cooling fans when conditions like 31.2°C and 60% humidity are detected, or to precisely adjust nutrient solutions based on suboptimal pH (5.8) and TDS (450 ppm) readings. This real-time adaptation, facilitated by defuzzification and aggregation, underscores the system's potential for precise resource control, leading to improved operational efficiency and reduced waste. The practical implications of this research are substantial, particularly for fostering sustainable agriculture. The developed system offers a scalable solution that promises to enhance plant growth and optimize resource utilization, making it especially relevant for small-scale farmers and burgeoning urban farming initiatives. By providing a robust, intelligent, and automated approach to hydroponic management, this study makes a valuable contribution to the field, positioning the proposed system as a promising tool for more efficient and environmentally responsible food production.

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