Team Members

Menna Emam

Team Leader

Shahd Khaled

Team Member

Mario Magdy

Team Member

Youssef sherif

Team Member

Supervisors

Dr. Walaa Elashmawi

Professor

Eng. Mohamed Abdelazim

Teaching Assistant

Abstract

Global waste generation has surged rapidly, with the annual production of over 2.01 billion tons of municipal solid waste and only 13.5% of it being recycled. By 2050, it is expected that global waste increases by 70%, risking serious environmental harm. This project aims to tackle the issue by developing a generative AI-based platform that helps individuals transform household waste–such as the annual 300 million tons of plastic waste generated –into AI-suggested DIY projects with creative designs and step-by-step directions. The platform can also be used by manufacturing plants, responsible for nearly 380 million tons of industrial waste in the U.S alone, to generate customized, sustainable product designs based on available materials. Durability reports can be viewed that assess product strength and carbon footprint. With deep learning and generative AI integration, the proposed solution promotes sustainability and contributes to reducing waste, supporting a circular economy.

System Objectives

1. To transform waste materials into innovative and functional products.

2. To harness AI technology to enhance creativity and practicality in product design, ensuring that designs are both unique and functional.

3. To promote sustainable design practices by encouraging the efficient reuse of materials, reducing waste, and fostering eco-friendly solutions.

4. To provide a seamless user experience by offering a step-by-step process, from material identification to product creation for both DIY and industrial applications.

System Scope

This project aims to create an AI powered platform that provides an innovative waste up-cycling solutions to two distinct groups; crafting enthusiasts and industrial users. In addition to providing individual users with innovative do-it-yourself upcycling ideas, the site will serve industrial customers by offering large-scale upcycling solutions that make use of leftover resources. Key deliverables include an AI model for waste-to-product generation, enabling tailored workflows for crafting enthusiasts and industrial users; engagement tools like chatbots for the crafters and a social hub for individuals who have completed DIY works to share their work and view other projects; environmental impact reporting targeted for the industries, estimating the impact on the environment and the durability of the designs.

Documents and Presentations

Proposal

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Technical

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Thesis

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Document

Presentation

Accomplishments

Publications

Competitions

Competition Title

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