INTEGRATED CROP PROTECTION SYSTEM

INTEGRATED CROP PROTECTION SYSTEM

1VAISHNAVI M, 2 KUSUMA B, 3 YAMUNA A K

Guide: Serin V Simpson, Assistant Professor CSE Department

Computer Science and Engineering, Presidency University, Bengaluru

DOI: 10.55041/IJSREM40521

Abstract

Farming is the backbone of human survival as it provides food for the increasing population. However, the sector faces problems such as plant diseases, bad selection of crops, and improper use of fertilizers that lead to lower yields and economic loss. We will introduce an AI-driven web app that integrates plant disease detection, crop suggestions, and fertilizer recommendations. The system applies advanced machine learning to analyse data while providing actionable insights to the farmers and researchers. In addition, it has an easy interface for them to navigate and implement plans of solution. The module for plant disease detection finds infections before they get severe via image processing, thus reducing losses through infections. The crop recommendation system suggests suitable crops that can be grown in consideration of environmental and soil data, resulting in better yields and sustainability for farmers. The fertilizer module provides data-driven guidance on optimal usage, minimizing waste and damage. It improves agricultural decision-making and boosts sustainability because of the proper predictions that help boost productivity, reduce risks, and ensure success for farmers.