Verdora

Inspiration

We were motivated by the high percentage of waste that is improperly disposed of or disregarded when they could serve a second purpose. Verdora solves the overconsumption and waste dilemmas heavily onset by 21st century capitalistic societies.

What it does

Using images uploaded by users, Verdora can analyze waste and properly sort items into navigable categories for further use or recycling. For waste products and recyclable goods, clients are directed to the proper distribution centers in their locality to effectively and efficiently enhance local waste management. Clothing items, pre-loved goods, and second-hand items can then be listed on the Verdora Marketplace, where clients can buy and sell various items

How we built it

We used React and Next.js for Frontend. For the backend we used Python, and connected the two with Fast API. Database was built using MySQL. Machine Learning was from open-source using TensorFlow and scikit.learn

Challenges we ran into

We had a couple merging conflicts as well as a first-year CompSci teammate, so some challenges were faced in the overall development process.

Accomplishments that we're proud of

The Machine Learning model was really hard to make so we feel confident in what we were able to complete given the hackathon's timeline

What we learned

Our first-year CompSci student was able to learn React for the Frontend development of our project

What's next for Verdora

Potential future developments would be integration with Smart Home technology to help minimize waste produced as well as successful waste categorization. Expanded AI capabilities and waste collection or pickup services may ease customer use of our platform as well.