Pest Detection System for Farmers
Year: 2025
Type: article
Abstract: This paper presents lightweight web-based pest detection software that aids in the early detection of crop pests using image classification techniques. The system is designed to support real-time predictions, user-friendly dashboards, and access control based on role-based logins. Built using React.js, Node.js, and MySQL, it can support up to 1000 user records with high efficiency. The software also integrates graphical visualizations using Recharts, helping users track pest prediction history and class distribution with confidence levels. This solution aims to improve agricultural productivity by offering a simple, accessible diagnostic tool for farmers, researchers, and agronomists.
Authors: Brundha Elci, Moulyashree S
Institution: Visvesvaraya Technological University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4410188173