Inspiration
We're a team of high school girls who love trendy fashion but we're unable to ignore what it's doing to our environment. Over the past decade, the fast fashion industry has grown tremendously--this industry encourages overconsumption and excessive waste. The average person buys 60% more apparel than they used to, and keeps it for half as long (World Resource Institute). Worse still, the environmental footprint of these clothing is huge. Globally, the fashion industry consumes an estimated 79 billion cubic metres of fresh water annually--the most water is used in the growing and production of fibers (UK Parliament Report). Just one cotton shirt uses 2700 liters of water; this is a person's drinking water for 2.5 years (World Resource Institute). The fashion industry is therefore exacerbating water scarcity globally especially in major cotton producing countries like India and Pakistan. These statistics are appalling--and, as much as we love buying cute dresses and jeans at affordable prices from fast fashion retailers like Forever 21 we knew we wanted to develop a technological tool that could help consumers just like us make sustainable choices when shopping.
What it does
That's why we developed fashiØn, a desktop app for online shoppers that will help them to quickly and efficiently track the water footprint of items they're considering purchasing. fashiØn helps users choose between different items of clothing by calculating the water footprint and suggesting the item with the least footprint. fashiØn takes the urls to the two clothing items the user is deciding between and the types of the clothing item (i.e., bottom, top, dress, jacket) as inputs from the user. Then, fashiØn scrapes the retailer website the user is shopping at to find the materials the garment is made of. fashiØn then calculates the water footprint of the two clothing items using a formula based on average weight of the clothing type and the water waste (gallons/lb) of the specific materials its made up of, and suggests to the user which item they should buy. Our mission is to streamline consumers' shopping process so that they can feel content, environmentally conscious, and fashionable.
How we built it
We used Electron to create a desktop application for online shopping that helps users become aware of garments' environmental footprint and guides them to choose stylish garments that use less H2O in production. We extracted data on materials in a garment from the retail website, then calculated water footprint based on material, and finally displayed which choice is more environmentally friendly.
Challenges we ran into
It was difficult to find standardized data for the fashion industry’s environmental waste since different stores likely had different values. Converting between and sending data in different languages was also an obstacle for us as we had to convert between HTML, Python, and Javascript. We also had trouble initially with implementing the web scraping and extracting relevant information.
Accomplishments that we're proud of
This was our first time using a web scraper and while it was difficult to extract the necessary information at first, we were able to experiment with various parser libraries in the process which enhanced our learning experience. We're also proud of building a presentable user interface with Electron in a limited time.
What we learned
-Webscraping, native web app development (Electron, Javascript, HTML/CSS etc.) -Converting between different languages and sending information -Designing UI/Branding for our app -Effective teamwork and collaboration
What's next for fashi0n
-Incorporating other environmental footprint measures (e.g., greenhouse emissions) -Allow users to track cumulative positive environmental impact and partnering with retailers who would like to reward consumers who are being environmentally conscious -Implement more efficient web scraping techniques and expand to other retail websites -Extend to mobile app functionality for in-store shopping
Log in or sign up for Devpost to join the conversation.