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This project presents a web application designed to bridge the gap between two critical entities: donors and individuals in need, including orphans and those requiring assistance of food . Utilizing the Random Forest algorithm in Machine Learning the food quality is checked and distributed to NGO's and orphanages.

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Excess-Food

OVERVIEW

TITLE: "Redistribution of consumable food by using Machine Learning."

ABSTRACT: This project presents a web application designed to bridge the gap between two critical entities:donors and individuals in need, including orphans and those requiring assistance. The application is divided into three primary segments: security and access control for donors, subscription options for supporters and event management for functions. Utilizing the Random Forest algorithm in Machine Learning, the project assesses food quality and predicts spoilage,enhancing the efficiency of food donations. Donors and recipients are seamlessly connectedwithin a defined radius, with recipients responding through the application. A comprehensive database tracks historical contributions and sends reminders for future events. Feedbackmechanisms and ratings ensure a fulfilling experience for donors. This project fosters a senseof community and philanthropy, facilitating a positive impact on society.

HARDWARE REQUIREMENTS:

• Processor: 1 GHZ or higher CPU • Hard disk: 500 MB available internal storage • Memory: 6 GB of RAM is minimally recommended • Display: 2.8 inches or larger

SOFTWARE REQUIREMENTS:

• Operating System: Windows 7 or above/Linux • Webserver: Django • Programming Languages: Python, CSS, Java Script • Web browsers: Google chrome/Mozilla Firefox/IE • Database: MYSQL • IDE: Visual Studio code

Instructions to run the project:

Commands:

  1. Extract the Zip file and paste into the D drive.
  2. Follow the below steps.

----> excessenv\Scripts\activate ----> cd ExcessFood ----> python manage.py runserver

  1. IP address will appear in the command prompt.
  2. Then copy-paste the IP address and paste it in the browser.

About

This project presents a web application designed to bridge the gap between two critical entities: donors and individuals in need, including orphans and those requiring assistance of food . Utilizing the Random Forest algorithm in Machine Learning the food quality is checked and distributed to NGO's and orphanages.

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