agric

Production-ready Smart Agriculture Backend with Spring Boot, JWT Security, ML Integration, and PostgreSQL.

This project implements a Prolog-based expert system for fertilizer recommendations, helping farmers optimize agricultural practices. It uses logical inference to suggest suitable fertilizers, improving crop yield and sustainability. The backend integrates with an existing frontend to provide a complete agricultural decision-making solution.

A crop and soil diagnosis platform for farmers that combines a React frontend and Node.js backend with computer vision and generative AI to analyze crop images and PDF soil reports, provide diagnoses, and support community Q&A.

The Fertilizer Recommendation System is a web-based application designed to provide tailored fertilizer recommendations for different crops based on various factors like growth stage, soil properties, climate, and more. It consists of a frontend built with React and a backend powered by Flask, using Prolog for inference.