Pest Detection System for Farmers

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

Publication Details

Journal
International Research Journal of Computer Science
Published
2025-05-08
DOI
https://doi.org/10.26562/irjcs.2025.v1204.10
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Pest Detection System for Farmers

Brundha Elci, S Moulyashree
International Research Journal of Computer Science
Smart Agriculture and AI
article

Pest Detection System for Farmers

Brundha Elci, S Moulyashree
article en

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.

International Research Journal of Computer ScienceVol. 12(04)
Openalex Percentile: Top 93%
Smart Agriculture and AI
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Pest Detection System for Farmers — Brundha Elci, S Moulyashree · International Research Journal of Computer Science (2025) | TGRS Research Map | TGRS