Intelligent Agricultural Hydroponic Production System

Abstract

This project presents an intelligent vertical hydroponic farming system that combines environmental control with automatic plant disease detection. The system is based on the ESP32 microcontroller and uses sensors to measure temperature and humidity, along with actuators such as a fan, heater, water pump, and LED grow lights. Environmental conditions are regulated using a fuzzy logic module to maintain an optimal environment for lettuce growth. For disease detection, a lightweight convolutional neural network (CNN) based on the MobileNetV2 model was trained on a dedicated dataset containing seven classes of healthy and diseased lettuce leaves. Real-time images are captured using a USB camera, allowing the system to react quickly to signs of disease. The system is designed to fit within vertical hydroponic farms, offering real-time monitoring and autonomous decision-making. The project aims to enhance crop productivity, reduce disease spread, and support smart and sustainable agriculture.