Inspiration
Fast fashion has a significant negative environmental impact. To put it into perspective, the industry is the second-largest consumer of water and is guilty for about 10% of global carbon emissions. That's more than all international flights AND maritime shipping bundled together. Yet, many consumers overlook this substantial cost to our planet in favor of convenience and affordability.
But what if there was a smarter way to shop? A way to quantify our choices and made us confront their real impact? To combat fast fashion, we can purchase higher-quality clothing that last us longer and become aware of the environmental consequences of buying internationally, cheap, and impulsively.
Vesta is here to make shopping more sustainable and environmentally friendly. Let's be kinder to our planet by checking the materials our clothes are made of, understanding how long they will realistically last, and measuring the environmental impact of every purchase.
Hasta la Vesta fast fashion!
What it does
Vesta quantifies the impact your fashion choices have on the planet and your wardrobe. It uses machine learning to measure out of a scale of 10 the quality of your clothes based on fabric, the weight of the fabric, assembly of the fabric (for example: knitted or woven), score care (how hard it is to maintain). It also measures how Eco-Friendly the clothes are through machine learning, this is quantified through x and x. Moreover, it estimates how long that piece of clothing will last you through units in years. It also uses a pie chart to help you visualize the composition of your garment. You can even hover over it to see more information on the fabric such as a description and the pros and cons.
Vesta is powered by AI to web scrape and parse the necessary data to display the information about your garment. {Josh}
How we built it
Challenges we ran into
Accomplishments that we're proud of
What we learned
What's next for Vesta
Vesta aims to provide the consumer with even more information in the future. Knowledge is power and knowledge is change. We want to add why we came up with these ratings and why our machine learning came to this conclusion. For example, you can hover over the estimated life of the clothes and find out why it believes that. Also, we want to add the care instructions and recommendations based on the fabric. Finally Vesta eventually will be able to suggest eco-friendlier alternatives to pieces that receive low ratings.
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