Trash Genius: AI Sorting Tech to Level Up Recycling Efficiency

inAI & Emerging Technologies

Background

This project introduces students to artificial intelligence (AI), image recognition, and data analytics to tackle a critical environmental challenge: inefficient recycling due to improper waste sorting. The goal is to create an AI-powered system capable of analyzing waste images and accurately classifying them for recycling, thereby reducing contamination in recycling streams and enhancing recycling efficacy.

Learning Outcome (LO)

  • LO #1: Introduction to AI in Environmental Solutions 
    Gain foundational knowledge of AI’s role in addressing environmental issues, with a focus on deep learning applications in waste management.
  • LO #2: Computer Vision for Waste Classification
    Develop skills in computer vision techniques for identifying waste materials based on features like labels, shape, and color, critical for accurate waste categorization.
  • LO #3: Data Analysis for Waste Stream Optimization 
    Learn to analyze waste composition data and identify patterns that inform more effective sorting and recycling practices, reducing contamination and maximizing recycling efficiency. 

What is on offer?

  • 1-on-1 sessions with Ph.D. Scholars
  • Supervision and Guidance from Global Faculty
  • Assistance in Publishing Research
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