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🌾 AgriTech: Smart Farming Redefined

Welcome to AgriTech!
An AI‑powered web platform designed to empower farmers with data-driven tools for smarter, more sustainable agriculture.

🚜 What It Does

  1. Crop Recommendation
    Suggests the best crops to grow based on soil nutrients (N, P, K), weather (temperature, humidity, rainfall), and pH.

  2. Yield Prediction
    Forecasts potential crop yields to help with planning and resource allocation.

  3. Disease Detection
    Scans crop images to identify diseases early using computer vision.

  4. Farmer Collaboration
    Lets farmers connect, share insights, and discuss best practices.

🧩 Why It Matters

AgriTech bridges the gap between traditional farming and modern insights. With tools like AI-driven recommendations, yield forecasts, and disease protection, farmers can:

  • Maximize their harvest with precision choices
  • Act quickly against crop diseases
  • Work smarter and sustainably
  • Build a community of shared wisdom

🛠️ Tech Stack

  • Backend: Python, Flask
  • Machine Learning: scikit-learn, NumPy, Pandas
  • CV: OpenCV (for disease detection)
  • Frontend: HTML, CSS, JavaScript, Jinja2
  • Environment: Virtualenv, requirements.txt for reproducibility

📂 Project Structure

AgriTech/
├── Crop Recommendation/        # Model training & scripts
├── Crop Yield Prediction/      # Forecasting scripts & notebooks
├── static/ & templates/        # CSS, JS, HTML
├── app.py or main.py           # Flask server
├── model files (e.g. crop . pkl)
├── requirements.txt            # Python dependencies
└── images/                     # Disease sample images

🏁 Getting Started

🔹 Clone the repo

git clone https://github.com/omroy07/AgriTech.git
cd AgriTech

🔹 Set up a virtual environment

python3 -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

🔹 Install dependencies

pip install -r requirements.txt

🔹 Run the app

flask run

Then visit http://localhost:5000 to explore features.

📈 Adding a New Feature?

  1. Fork the repo & create a branch:
    feature/your‑feature

  2. Build, test, and document your changes

  3. Push your branch and open a Pull Request

We'll review your work and help merge it 😊

🧪 Tips for Improving AgriTech

  • ✅ Database Connection (see Issue #4)
  • ✅ Polish the front-end design (see Issue #4)
  • 🤖 Integrate a chatbot using a small LLM (see Issue #3)
  • 📊 Add a detailed yield prediction system (see Issue #2)
  • 🧠 Expand crop recommendation logic and UI (see Issue #1)

💡 Want to Learn More?

Curious about the inner workings—like how model training, data pipelines, or image analysis tie together? Dive into the notebooks found in the Crop Recommendation and Yield Prediction folders!