Inspiration
We wanted to make a product that related to sustainability and that any individual could use. Based on those goals, we researched where individuals' carbon footprints usually come from. When we found that diets play a major role, we decided to make a user-friendly web application that could help a person understand the environmental impacts of the foods they eat.
What it does
A user inputs the ingredients from their meal - whether it be a fruit smoothie for breakfast or spaghetti and meatballs at dinner with a glass of wine. The application then returns the total emissions from the ingredients in the meal, as well as a table with a breakdown of each individual ingredient's carbon emissions and where those numbers are coming from (farming, processing, etc.). It also displays a pie chart for easy comprehension of that ingredient-emissions breakdown.
How we built it
We used IBM-Z Systems to work on our code as a team (password is carbon if you check it out from the link). It helped us to split up jobs and collaborate in real-time, seeing others' changes quickly and clearly. We coded the backend primarily with Python, using Flask for web development and the pandas library to organize and manipulate our data. We used HTML, css, and javascript, and bootstrap for the frontend.
Challenges we ran into
Originally, we wanted to make use of the CloudCarbon API that provides information about the carbon emissions of foods. However, a few hours in, we realized that they were not going to provide us with a password in time to access their API. We'd already come up with a wireframe and brainstormed the functionality of our web application, so we didn't want to change our entire plan. Instead, we decided to use a small dataset we found to initially implement our app.
Accomplishments that we're proud of
We are proud of our UI, as it's clear, concise, and user-friendly. We are also proud that we were able to pivot when we ran into the API challenge, and of our idea in the first place!
What we learned
We all learned a ton: how to use IBM-z systems, how to use flask, how to pass variables from backend to frontend, and how to deal with merge conflicts on github.
What's next for Recipie Carbon Footprint Calculator
We want to incorporate the CarbonCloud API when we get access, as it will hugely expand the amount of data we can supply for the user. Additionally, we'd like to recommend alternative ingredients that result in less carbon emissions, based on a user's specific meal. E.g., oat milk instead of dairy milk, or low-emissions meats instead of beef.
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