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The project includes various scripts and SQL files to manage and analyze food surplus and recipient data. It leverages Python for data processing, SQLAlchemy for database interactions, and machine learning models to predict food waste. The system aims to efficiently redistribute surplus food to NGOs and other recipients and minimizing food waste.

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NoWon1/Food-Waste-Reduction-and-Redistribution-System

 
 

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Food Waste Reduction and Redistribution System

A Python-based system designed to efficiently manage and redistribute surplus food to those in need while minimizing food waste.

Features

Database Management:

Uses MySQL for storing and managing food surplus, donor, and recipient data

User Authentication:

Secure login system for donors and NGOs

Food Waste Prediction:

ML-based prediction model for food waste estimation

Automated Matching:

Intelligent matching of food donors with recipient NGOs

Nutritional Analysis:

Integration with USDA API for nutritional information

Real-time Updates:

Live tracking of food availability and redistribution status

Tech Stack

  • Python 3.11
  • MySQL Database
  • SQLAlchemy ORM
  • Machine Learning Libraries
  • USDA Food Data API

Setup

  1. Clone the repository
  2. Install dependencies:
pip install -r requirements.txt
  1. Configure database settings in main.py:
DB_CONFIG = {
    'host': 'localhost',
    'user': 'your_username',
    'password': 'your_password',
    'database': 'food'
}

Project Structure

main.py:

Main application entry point and database configuration

data.py:

Data processing and management

predict.py:

ML model for waste prediction

route.py:

Route optimization for food distribution

nutri.py:

Nutritional analysis integration

SQL files:

Database schema and queries

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the MIT License - see the LICENSE file for details.

About

The project includes various scripts and SQL files to manage and analyze food surplus and recipient data. It leverages Python for data processing, SQLAlchemy for database interactions, and machine learning models to predict food waste. The system aims to efficiently redistribute surplus food to NGOs and other recipients and minimizing food waste.

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  • SQL 57.1%
  • Python 42.0%
  • Groovy 0.9%