Demo video

Foreword

  • My first Year Long project in ISDN Major
  • I am the leader of a team of 5 passionate students
  • We practiced Design thinking process and product prototyping process

Project Details

Problem

  • We discover that in Hong Kong when you throw 100 plastic bottles into recycle bin, only 4 of them is actually recycled
  • We interviewed different industry leaders to get more insights
  • We found 3 mean causes
    • It is expensive to process plastic - Multiple types of plastic requiring different processing plant to properly recycle. Too expensive to filter out other types of plastic and then send to another processing plant.
    • High transportation cost - The bottles are not compressed when they are being transported, leading to the truck transporting mostly air, instead of plastic. Plastic per truck is too low
    • Contamination - Small contaminents like water or coke will ruin the entire batch of plastic bottles
  • We asked “Why not install compressors in recycle bin? It will increase the ‘Plastic bottle per truck ratio’.”
    • Ans: If we compress the bottle, and it has liquid inside, it ruins the entire batch of plastic and also cuase hygene problems.

Solution

  • We went through the ideation process iteratively to arrive in the final solution
  • A smart recycle bin consist of 3 main component to solve the problems
  • Components
    • Computer vision system (CV)
      • Computer vision (CV) system that identifies contaminants inside bottles and would reject the bottle if they are detected
      • The CV system combines with weight sensor to estimate the expected weight of the bottle
      • If the actual weight exceeds the expected weight, we reject the bottle
      • This systems works for non-transparent bottles


  • NIR spectrometer
    • We use NIR spectrometer to identify the type of plastic
    • We sort the plastic at the source, so that there is not “Second stage transportation”
    • Alt text
  • Mechanical Compressor
    • We compressor that shrinks the volume of bottles after it is identified to be clean
    • Due to safety concerns, we did not implement it in the lab prototype

Computer Vision System

  • I was in charge of developing the computer vision system
  • I have built my own dataset of 5000+ images
  • Built and trained my own model using Tensorflow and Keras
  • The following is a snippet of my technical research report