Skip to content

Latest commit

 

History

History
71 lines (52 loc) · 2.06 KB

README.md

File metadata and controls

71 lines (52 loc) · 2.06 KB
Raw

🌾 AgroSmart Project

AgroSmart is an intelligent agricultural management system designed to optimize farming decisions through machine learning. By consolidating soil nutrient analysis, rainfall data, crop recommendations, and yield predictions, AgroSmart enhances decision-making for farmers, helping them select the best crops and forecast yields accurately. The system also integrates a Virtual Market for organic products, enabling interactions between visitors, officers, and sellers.

📋 Table of Contents

🛠️ Technologies Used

  • Backend: Django, Python
  • Frontend: HTML, CSS, JavaScript, Bootstrap
  • Machine Learning: Models for crop recommendation and yield prediction

🌟 Key Features

  • Soil & Rainfall Data: Provides comprehensive insights for better crop decisions.
  • Crop Recommendation & Yield Prediction: Boosts crop yield by 20%.
  • Virtual Market: Facilitates transactions and connects users for organic product sales.
  • Secure Logout: Ensures safe user session management.

🚀 How to Run the Project

Prerequisites

Python installed on your system. Virtual Environment: Recommended to isolate dependencies.

Setup

  1. Clone the Repository:

    git clone https://github.com/1-Sanchit-1/AgroSmart.git

  2. Create a Virtual Environment:

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

  3. Install Dependencies:

    pip install -r requirements.txt

  4. Run Migrations:

    python manage.py makemigrations
python manage.py migrate

  5. Create a Superuser:

    python manage.py createsuperuser

  6. Load Initial Data (if any):

    python manage.py loaddata initial_data.json

  7. Run the Development Server:

    python manage.py runserver

  8. Access the Application: Open your browser and go to http://127.0.0.1:8000/.