Our solution to end the world hunger one crop at a time is to connect surplus of food to those who are in need.
Annona, derived from Cura Annonae (an ancient Roman term for 'care of the grain supply'), was inspired by the growing challenges faced by farmers and impoverished communities in wake of the COVID-19 outbreak.
Annona recognizes socioeconomic impacts of COVID-19 pandemic on the food industry. We are using data sets from the United States Environmental Protection Agency about food loss and waste to understand the severity of these issues prior pandemic so that we can project how much the food accessibility and distribution will be impacted after the pandemic.
Python was used to represent data from http://www.fao.org/food-loss-and-food-waste/flw-data/en/
Why are we focusing on food waste and loss? Our motivation https://www.epa.gov/facts-and-figures-about-materials-waste-and-recycling/food-material-specific-data
Food loss and waste data was obtained from Food And Agriculture Organization of the United Nations to see the results of food loss and waste around the world. Obtained data was later narrowed to United States only for simplification purposes (check foodloss.csv US tab) where only highlighted columns were the main point of attention.
Data obtained from the given sources impacted our project because we were able to identify what food sources were the most subjected to waste. Most of which are popular among consumers such as dairy, nuts, etc. Also, data from this project showed us past historical trends and how that will incorporate into 2020 and post COVID-19. In the future, we are planning to use the data obtain to predict how much food waste will be affected by the pandemic.
Our web platform was built with JavaScript, Node, PostgreSQL, React, and AWS. Data analysis was conducted using Python using plotly package to represent data from FAO (Food Loss and Waste Database). Our tool for graphic design was Adobe Illustrator. For our slides presentation, we used Google Slides.