Inspiration

Andrew really wanted to learn object identification so, after a little bit of research on the insane amount of wasted resources & money spent on food, we ended up settling on applying machine learning to fridges.

What it does

Essentially, it's a fridge that uses computer vision & machine learning to help you waste less food by analyzing how much of your food typically goes bad and then suggesting you buy less food next time you're at the market.

How we built it

We used HTML, CSS, JavaScript for the front-end. We used Python & TensorFlow for the machine learning part. We used Node.JS for the back-end.

Challenges we ran into

This is a lot of our 1st hackathons so we didn't really know what to do for the first several hours. This wasted time ended up resulting in 2 of us having to stay up all night to try to even build a semblance of a product.

Accomplishments that we're proud of

We learned a LOT & managed to accomplish a lot considering most of us are 1st-timers.

What we learned

No one in our team has had any prior experience in the fields they worked in for this project. It's fair to say that we literally learned everything during the process of coding.

What's next for Green Savings

We'd like to continue working on all the different aspects of our code just to see where it takes us.

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