Crop Recommendation System
This project is an AI-powered web application designed to assist farmers in making informed crop choices based on various inputs such as region, soil type, investment amount, and available resources.
Usage: https://agrivision-innovators.streamlit.app/
Features
User Authentication (Sign up and Login)
Region and Soil Type Selection
Seasonal and Financial Inputs (investment, area, ROI expectations)
Resource Specification (water, fertilizers, machinery, labor)
Real-time Weather Data Integration (OpenWeather API)
Static Agricultural Data (Historical crop prices and stats for India and Pakistan)
AI-powered Crop Recommendations (Meta-Llama 3.1 LLM)
Detailed Suggestions on Projected Return, Investment Ratio, and Risk Level
Interactive UI with expandable recommendation sections
Technologies Used
Streamlit for building the web interfaceMeta-Llama 3.1 hosted on the Together platform for generating crop recommendationsOpenWeather API for real-time weather dataPython for backend logic and data processing
How it Works
Users provide region, soil type, and resources available.
The application uses real-time weather data and static agricultural data to generate personalized crop recommendations.
Each recommendation includes projected returns, investment ratios, and associated risks.
