As our team has members from all over the world, we wanted to create a product that adressed a problem everyone was passionate about. We noticed that everyone was affected by the state of our environment, and so we wanted to present a solution that was sustainable and would inspire women to make a difference. Envirno was that solution - by showing you ideas on how to reuse everyday items, it makes sustainability exciting.

What it does

Envino is a web app that uses your web camera to recognize an object. It then gives you suggestions on how to reuse that to limit the amount of waste that goes into landfills. Additionally, it spotlights female entrepreneurs that are combating this crisis through innovative products and supports their small businesses.

How we built it

We used a combination of HTML/CSS/JS to build the actual website. These languages help with building each of our different features as well: our Scanning Cam, Donation function, etc. Our Scanning Cam was additionally created with a teachable machine. So machine learning algorithms were added to our website as well.

Challenges we ran into

We had some issues with keeping in touch with everyone - since the time difference between some of our members was so large, it meant we all stayed up late into the night to get this project finished. Arranging the dividers in the html document was also a bit of an issue as well. Then we had some issues with our camera function working for our scans but we were able to get it fixed just in time.

Accomplishments that we're proud of

We are proud of how usable the product is - the clean and engaging user interface was something we worked really hard on, so that being sustainable didn't feel like a chore. Additionally, we’re proud of having our arrangement of the website fixed, the amount of features we were able to implement in 24 hours, and implementing state of the art machine learning algorithms into our technical solution.

What we learned

We learned A LOT about javascript and the functionality it can add to a website. This especially came in handy with our donation feature and our scanning can feature. Some of our team members also got to work with teachable machines for the first time which was a really interesting and rigorous process. We definitely improved our collaboration and time management skills.

What's next for Envino

Our next steps entail making our application more accessible to the public. This includes making our website feasible from the screen of a phone as well as creating a mobile application for our website.

We expect our main feature, our Scanning Webcam, to be created into a API and deployed to furniture companies using IoT technology to build better furniture. This way our solution can be incorporated as an Internet of Things device that can be used by any family who buys furniture from these companies.

We want to improve the machine learning we use to detect objects. If it could recognize more materials, it would be able to tell if the product is compostable, recyclable, or should be repurposed some other way. With more time, we wanted to spotlight more small businesses so that we can spread the impact they make.

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