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AI in Recycling

Nicholas K.

By using a machine learning algorithm, we have been able to create a tool that can detect what type of material an item is and determine whether it is recyclable or not.


The plastic pollution issue is an issue that has been plaguing the earth for the past half century and longer. Despite this, it has only been brought to light in the 21st century, and technology to help solve the issue is still new and largely undeveloped. Being someone who is passionate about environmental conservation, I wanted to create a tool that could be used to more easily sort recycling items. By using a machine learning algorithm, we have been able to create a tool that can detect what type of material an item is and determine whether it is recyclable or not. This tool can be applied to many different industry sectors, whether it is sorting items in a recycling plant, building it into an app for people to use day to day, or even aiding the plastic oceans cleanup effort. By creating this tool, we help do our part in protecting our planet and helping those who are less educated in the field to do so as well. We have approached the problem by using various machine learning algorithms to identify the material of items in a dataset. Using a KNN and CNN algorithm, we created a tool that became more and more accurate in identifying the material of an item. After testing the KNN and the CNN algorithm, we found that the CNN algorithm was much more accurate reaching a 68 % accuracy compared to 46% accuracy

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Nicholas K.
Shreyas Muralidharan
PhD Candidate in Electrical and Electronics Engineering at Stanford

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