Swati-0301/Edge-AI-in-Farming-Smart-Farming-Project

# 🌿 Edge AI in Farming – Plant Disease Detection ## 📌 Overview Plant diseases significantly impact agricultural productivity and global food security. Early detection of plant diseases can help farmers take timely action and reduce crop losses. Traditional disease detection methods rely heavily on manual inspection, which is time-consuming and requires expert knowledge. This project implements an AI-based plant disease detection system using **deep learning and computer vision** to automatically identify plant diseases from leaf images. Such automated systems can assist farmers by providing faster and more accurate diagnoses. The implementation is inspired by the research paper: pmc.ncbi.nlm.nih.gov --- ## 🚀 Features * 🌱 Automated Plant Disease Detection * 🧠 Deep Learning-based Image Classification * 📷 Detects diseases from leaf images * ⚡ Fast predictions using trained models * 🌾 Supports smart agriculture applications * 🧩 Can be integrated with Edge AI devices or mobile applications --- ## 🧠 Project Motivation Plant diseases are one of the main causes of reduced agricultural yield. Many farmers depend on manual observation or expert consultation, which may be slow and inaccurate. Recent advancements in **machine learning and deep learning enable automatic disease detection through computer vision**, making crop monitoring faster and more efficient. This project aims to: * Assist farmers in early disease identification * Reduce crop losses * Support precision agriculture systems --- ## 🏗 System Architecture ``` Leaf Image │ ▼ Image Preprocessing │ ▼ Data Augmentation │ ▼ Deep Learning Model Training │ ▼ Disease Classification │ ▼ Prediction Output ``` --- ## 🔬 Methodology ### 1. Data Collection Plant leaf images dataset containing healthy and diseased leaves. ### 2. Preprocessing * Image resizing * Normalization * Data augmentation ### 3. Model Training * Convolutional Neural Networks (CNN) * Transfer learning m …