Smart Crop Management System

An AI-powered agricultural advisory platform for farmers, combining crop advice, pest detection, farmer profile management, and history tracking in a mobile-responsive web interface. Built with React, FastAPI, and MongoDB.

---

🚀 Overview

Smart Crop Management System is designed for modern agriculture. It empowers farmers by providing:

• AI-driven crop recommendations tailored to location, crop type, and language.
• Instant pest and disease detection via image analysis.
• Personalized farmer profiles for ongoing support.
• Advice history tracking for continuous learning and smarter decisions.

Originally developed as a hackathon project, the platform puts smart, actionable insights within every farmer’s reach.

---

📦 Project Structure

smart-crop/
│
├── backend/           # FastAPI backend for APIs, AI, database, integrations
│   ├── server.py
│   ├── requirements.txt
│   └── ...
│
├── frontend/          # React + Tailwind CSS frontend for the web app
│   ├── src/
│   │   ├── App.js
│   │   └── ...
│   ├── public/
│   ├── package.json
│   └── ...
│
├── tests/             # Test scripts for backend and frontend
│   └── __init__.py
│
├── .emergent/         # Configuration for AI/LLM agent and integrations
│   └── emergent.yml
├── .gitignore
├── README.md
└── test_result.md

---

🛠 Tech Stack

• Frontend: React 19, Tailwind CSS, Radix UI, Axios
• Backend: FastAPI, Pydantic, Motor (async MongoDB), dotenv
• AI/LLM: emergentintegrations, OpenAI GPT-4o mini
• Database: MongoDB (async)
• Other: PIL (image processing), CORS, Docker-ready structure

---

⚙️ Features

• AI Crop Advisor: Natural language Q&A powered by GPT-4o mini, returns localized, crop-specific advice.
• Pest Detection: Upload crop images for instant AI-driven pest/disease diagnosis & recommendations.
• Farmer Profile: Store and manage info—name, location, farm size, primary crops, phone.
• Advice History: See all past questions and answers for reference.
• Mobile-First Responsive UI: Clean, intuitive interface for phones and desktops.

---

🚦 Getting Started

Prerequisites

• Node.js, Yarn or NPM for frontend
• Python 3.9+ for backend
• MongoDB database (local/cloud)
• OpenAI and Emergent API Keys for AI features

Backend

cd backend
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
# Set up environment variables in .env (see below)
uvicorn server:app --reload

Environment variables (.env):

MONGO_URL=mongodb+srv://<user>:<password>@cluster0.mongodb.net/<dbname>?retryWrites=true&w=majority
DB_NAME=smartcrop
EMERGENT_LLM_KEY=your_emergent_api_key
CORS_ORIGINS=http://localhost:3000

Frontend

cd frontend
yarn install
yarn start

Configure REACT_APP_BACKEND_URL in a .env file if needed.

---

🧩 API Overview

• POST /api/crop-advice — Get AI crop advice
• POST /api/pest-detection — Analyze crop image for pests
• POST /api/farmer-profile — Create new farmer profile
• GET /api/farmer-profiles — List all profiles
• GET /api/advice-history — Advice history for user

More API details: See backend/server.py

---

📱 UI Features (Run frontend)

• Home: Quick access to core features
• Profile Form: Interactive form input and validation
• AI Chat: Ask any agri-question, instant replies
• Pest Detection: Upload/camera, see results and next steps
• History: Timeline of all Q&A, easily browsable

---

🧪 Testing

• Automated and manual tests in /tests and test_result.md
• Run tests and see the current testing state (priority, implemented features, etc.)

---

📝 Contributing

Pull requests, issues, and feature requests are welcome!

---

📄 License

MIT (or specify your license here)

---