Turmeric plant Disease Monitoring using Internet of Things and Computer Vision

This paper presents a solution to address persistent challenges in Indian agriculture by advocating for the implementation of an IoT model integrated with machine learning algorithms. The proposed system aims to automate irrigation practices tailored to turmeric cultivation by collecting and analyzing crucial data such as soil moisture, air humidity, and temperature using sensors. Additionally, the system detects diseases in turmeric plants and monitors soil acidity levels using a three-way soil meter integrated with an HX711 amplifier. Leveraging cutting-edge technologies like YOLO v5 for disease detection and ESP32 for image capture, the system sends data to Google Drive for analysis by machine learning models. Soil moisture data collected by a DHT11 sensor is transmitted to an Arduino for controlling a solenoid valve for irrigation, then sent to an ESP8266 for publishing on the ThingSpeak server for monitoring. This integrated approach aims to optimize turmeric yield, promote sustainability, and improve efficiency, contributing to the evolution of the agricultural landscape in India.