FARM GUARD: An IoT-Based Smart Agricultural System For Automated Irrigation, Crop Recommendation, and Plant Disease Detection Using ESP32

Abstract

Agriculture faces several challenges, such as inefficient water management, improper crop selection, and delayed detection of plant diseases, which reduce crop yield and farmer income. To address these issues, this study presents an IoT-based smart agriculture system developed using the ESP32 web server platform.  The proposed system integrates automated irrigation, crop recommendation based on predefined soil pH reference data, and image processing-based plant disease detection.  Soil moisture is continuously monitored, and irrigation is automatically controlled to maintain optimal water conditions, thereby reducing water waste.  Suitable crops were recommended using stored soil pH reference values.  For plant health monitoring, leaf images collected from agricultural fields and uploaded into MATLAB were analyses using image processing techniques to identify early disease symptoms.  All important system information, including sensor readings, irrigation status , crop recommendations and disease detection results, was displayed in real time through a web-based dashboard.  The experimental results demonstrate that the proposed system improves resource utilization, supports precision farming, and assists farmers in making informed decision regarding sustainable agricultural practices.