Our Inspiration
Looking to create a sustainable environment, our project will allow users to determine the carbon emissions associated with everyday tasks. We noticed that current online resources lacked a complete carbon emission report, giving the simplified emission by generalized food groups or by specific ingredients. To raise awareness of an individual’s carbon emissions, FoodPrint focuses on creating a workflow that allows users to calculate their estimated Carbon Dioxide emissions more efficiently.
What it does
Our project allows users to input dishes and be able to identify their overall CO2 emissions in grams per dish serving size.
How we built it
To tackle the problem, we focused our model on two different objects: dishes and ingredients. Each dish has a set of ingredients with their respective amounts. Each ingredient has its own set of information regarding its name and general carbon footprint--the measure of carbon emissions during its lifecycle from cradle to grave.
The app utilizes 3 separate database queries to determine the overall CO2 emission of the dish. Edamam API: Allows for easy lookup of dishes within a recipe’s database, in which users can choose from after querying their dish.
Carbon Emissions per Serving and per Calorie Database: Provided key information on 96 common ingredients, and their carbon emissions in grams per serving.
NDB Food Search API: Provided food category information per ingredient, allowing for greater generalizations of specificity in different parts of the app implementation
Challenges we ran into
Our Carbon Emissions per Serving and per Calorie Database was limited to only 96 ingredients and their footprints. In certain examples, such as “chili peppers” or “cream cheese” the database had very little information on. In these cases, we resorted to determining the food group and making a generalization of its carbon footprint based off of the median of all items within the food group (provided by the 96 ingredients).
Recipe items with their amounts were given in one string line. The way in which recipe measurements were given were not uniform, making it hard to isolate the recipe name from its unit of measure
Certain food items had more complex names, along with qualitative measurements, such as “measure to taste” for salt. This, in certain edge cases, prevented our food group query from determining the food group of those ingredients.
Accomplishments that we're proud of
Created a working app that has basic functionality, capable of determining carbon emissions
What we learned
We identified the difficulties of determining GHG emissions and the limitations of our data, as different food items, and even similar food items can have drastically different life cycle’s.
What's next for FoodPrint
In understanding the limitations of our data set, we want to find a more comprehensive ingredients -> CO2 database, or utilize provided government data to calculate carbon footprints for a variety of ingredients.
We wish to give more control to the users in the app to customize recipes, being able to edit ingredients and add their own as well as delete ingredients accordingly.
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