Automatic Plant Watering and Disease Detection System

The agro ecology is one of the most important topic in now a day's scenario which means the interaction between man, nature and plants. /the work here introduces a comprehensive solution for automated plant management by integrating automation and deep learning. The system automates irrigation using an Arduino microcontroller, soil moisture sensor, relay, and water pump to ensure plants receive adequate water when moisture levels fall below a set threshold. For disease detection, a Convolutional Neural Network (CNN) model developed using TensorFlow and Keras analyzes leaf images to predict plant health conditions. A Flask-based web application allows users to upload leaf images, enabling accurate disease diagnosis with detailed prevention measures and treatment recommendations. Additionally, the web application displays real-time soil moisture data and notifies users about watering needs. This system aims to reduce manual labor, improve plant health monitoring, and enhance agricultural productivity. Future improvements include extending the system to support a wider variety of plants and diseases while enhancing scalability and automation features.