IoT-Based Automated Hydroponic System For Precision Lettuce Growth Management

Abstract

Hydroponic lettuce cultivation requires continuous monitoring and regulation of environmental and nutrient conditions to ensure optimal plant growth and productivity. However, manual monitoring can be labor-intensive, time-consuming, and prone to human error. This study aimed to design, develop, and evaluate an IoT-Based Automated Hydroponic System for Precision Lettuce Growth Management that provides real-time monitoring and automated environmental control. Specifically, the system monitors temperature, humidity, pH level, electrical conductivity (EC), and water level while providing remote access through a web-based dashboard. The study employed a developmental-descriptive research design and followed the Agile Software Development Life Cycle (SDLC) in the design, development, and testing of the system. An ESP32 microcontroller, sensors, and cloud-based technologies were integrated into the prototype. Fuzzy logic control was applied to regulate temperature and humidity through automated misting and exhaust fan operations, while threshold-based control was utilized for pH and EC management. The system was evaluated by 30 purposively selected respondents consisting of IT professionals, agricultural experts, and hydroponic farmers using the ISO/IEC 25010:2011 Software Quality Model. Results revealed an overall mean score of 4.63 (SD=0.56), interpreted as Very Good. Usability and Interaction Capability obtained the highest mean score (4.75), followed by Functional Suitability (4.69), Portability (4.64), Performance Efficiency (4.49), and Reliability (4.46). The findings indicate that the developed system is functional, efficient, reliable, and user-friendly. The study concludes that the IoT-based automated hydroponic system effectively supports precision lettuce growth management, reduces manual intervention, and promotes sustainable agricultural practices.