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Agrimax

Agrimax is a comprehensive Crop Recommendation and Field Management System designed to empower farmers with data-driven decisions for better crop yield and farm management. It integrates soil health analysis, weather forecasting, and crop recommendation to help users make informed agricultural choices.

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Features

• Crop Recommendation: Suggests the best crops to grow based on soil nutrients, environmental factors, and local weather data.
• Soil Health Analysis: Evaluates soil health and provides actionable suggestions to improve fertility and productivity.
• Weather Forecasting: Offers real-time weather insights for better planning.
• Farm Management: Tracks farm history, crop rotations, and nutrient usage for optimized farming practices.
• User-Friendly Interface: A web interface designed for ease of use by farmers.

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Technologies Used

• Frontend: HTML, CSS, JavaScript (Tailwind CSS for styling)
• Backend: Python (Django Framework)
• Database: SQLite / PostgreSQL
• APIs: Weather API integration for real-time forecasting
• AI/ML: Machine learning models for crop recommendation and soil analysis

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Dependencies

This project relies on the following Python packages and modules:

• Core Libraries:

  • numpy
  • pandas
  • datetime
  • os
  • json
  • pathlib
  • time

• Data Science and Machine Learning:

  • sklearn (datasets: make_classification, preprocessing: MinMaxScaler)
  • joblib

• Visualization:

  • matplotlib.pyplot
  • seaborn

• Web Framework and Utilities:

  • django.conf (settings)

• Geolocation and Requests:

  • requests
  • geopy (exc, geocoders: Geocodio, GoogleV3, Nominatim, OpenCage)

• Custom Modules:

  • get_coordinates (get_latitude_longitude)

• Configuration Parsing:

  • configparser

Dependency Graph

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Installation

Prerequisites

Ensure you have the following installed on your system:

• Python 3.8 or higher
• pip (Python package installer)
• Node.js (optional, for frontend builds)

Clone the Repository

git clone https://github.com/skye-cyber/Agrimax.git
cd Agrimax

Backend Setup

1. Create and activate a virtual environment:

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

2. Install dependencies:

   pip install -r requirements.txt

3. Run database migrations:

   python manage.py migrate

4. Start the server:

   python manage.py runserver

Frontend Setup (Optional)

If you're working on the frontend, navigate to the frontend folder and install dependencies:

cd frontend
npm install

To build the frontend:

npm run build

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Usage

1. Access the application locally at http://localhost:8000.
2. Register or log in to start using the features.
3. Input soil data, weather parameters, or manage farm details to receive recommendations.

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Contributing

We welcome contributions to make Agrimax even better! Follow these steps to contribute:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature-name

3. Make your changes and commit them:

   git commit -m "Added new feature"

4. Push to your forked repository:

   git push origin feature-name

5. Open a pull request in the original repository.

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License

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <https://www.gnu.org/licenses/>.

See the LICENSE file for more details. See the LICENSE file for details.

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Contact

For questions, feedback, or support, feel free to reach out:

• Email: [email protected]
• GitHub: skye-cyber

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Thank you for choosing Agrimax! Together, let's make farming smarter and more efficient.