Published Paper Details:

Agriculture is a cornerstone of India's economy, employing a vast portion of the population. To meet increasing food demands, it is essential to enhance farming practices. Advanced technologies like machine learning (ML) and deep learning (DL) offer the potential to significantly boost agricultural productivity through early crop disease detection and optimized resource use. Our project, AgriSmartHub, utilizes ML techniques such as KNN, SVM, and DL methods like CNN to detect plant diseases swiftly and accurately. By training these models on extensive datasets, they effectively identify patterns and predict diseases. Specifically, our DL system automates the scanning of leaf images to identify diseases based on visual symptoms, assesses disease severity, and recommends suitable fertilizer quantities. A user-friendly interface allows farmers to easily capture leaf images and receive insightful, tailored suggestions, aiding in improved crop production and quality. AgriSmartHub empowers farmers to make informed decisions and optimize yields.