- You are simply more likely to recycle if you have to think less to do so
- A huge problem with the recyclying industry is that when one piece of trash is in a recycling bin, the entire bin must be thrown out
- These two problems lead to the current failure of our recycling system and solving for this can spur true environmental progress
- The feeling of uncertainty when you are faced with a bag of chips and an intimidating abundance of cans to decide from is why we created this app
- Rather than being forced to make an impulsive, and often incorrect, decision, we'd like to make the right decision for you.
- User takes a picture of a disposal good and the application displays the most likely categories of recyclable or trash along with confidence values for each category
- Uses a Convolutional Neural Network to classify different types of waste based on a Kaggle dataset of thousands of images
- Hosted this web app on a Heroku server and connected this with an interactive UI
- Implementing Heroku and connecting our frontend to our AI backend were, without a doubt, the most difficult parts of this projects
- We are proud of my neural network's ability to classify images into 6 different groups with such a high accuracy
- We are also very proud in our Heroku server and its ability to dynamically hold and conduct our AI operations to each of our images
- We learned about the many different ways to maximize the accuracy of a neural network
- We also learned how to host and upload images to a Heroku server
- Integrating our software in hardware that can be installed near recyclying bins to make it extremely convinient to recycle
- Creating a mobile app so more people can actively classify different types of waste regardless of their vicinity to a recycle bin
- Rahul Shah & Varun Nair
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