Journal of Artificial Intelligence, Machine Learning and Soft Computing

Authors: V. P. Kharge, Shreya Sadanand Dalwai, Madhavi Sanjay Gurav, Shraddha Uttam Jong, Sejal Arvind Mane

Abstract: LeafScan: AI Assistant for Farmers is a groundbreaking project aimed at revolutionizing agriculture by empowering farmers with advanced technology. This project combines a web application and a chatbot, termed "Farmers Assistant," to provide farmers with a comprehensive solution for identifying and managing plant diseases. Utilizing Python, LeafScan employs a deep learning model tailored for classifying plant diseases based on user-uploaded images. The model, derived from deep learning techniques, preprocesses images and offers the top five predictions with associated class labels, probabilities, and confidence scores, ensuring accurate disease identification. LeafScan also aims to enhance disease detection capabilities through the development of a Convolutional Neural Network (CNN) model. Additionally, the project emphasizes the importance of a user-friendly interface, utilizing HTML, CSS, and JavaScript, to facilitate seamless interaction for farmers. Furthermore, the Farmer's Assistant chatbot is poised to provide holistic support beyond disease identification, catering to farmer queries and offering comprehensive agricultural assistance. LeafScan stands at the forefront of leveraging AI to address real-world challenges in agriculture, promising significant advancements in crop management and sustainable farming practices.

Keywords: LeafScan, AI Assistant, Plant Diseases, Deep Learning Model, Farmers Assistant