Smart Agriculture Assistant with Chatbot and Disease Detection
Year: 2025
Type: article
Abstract: Agriculture is an important sector that feeds the economy and creates food security; however, farmers face challenges with access to timely information, proper crop management, and insufficient tools for early disease detection. This project describes a Smart Agriculture Assistant system consisting of a chatbot, database, and image analysis system that allows a farmer to engage with each system as a single point of contact. An ‘AI’ Chatbot that utilizes a text generation API provides farmers with immediate feedback to questions on growing practices, fertilizers, pesticides, and irrigation. A structured crop management database supported by Flask and MySQL, captures detailed information about the crop, including fertilizer, pesticides, pest problems, and growth stage of the crop, and has an admin panel for editing purposes. An image analysis system powered by convolutional neural network (CNN) models primary functions to identify plant disease using the leaf image of the crop. All three systems work together to improve predicaments, limit the amount of loss, and establish sustainable agriculture.
Authors: Sabitha K, Abisheak S, Deepak S, Dharsan N, Hariprasath SK
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W7106168217
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