Well, as our project is based on the prevention of long-term hunger risks, because of that, we studied the food route and decided that the best way, in fact, is to consciously ration, based on regional data
Our team tried to adopt the data provided to study in which regions the problem was more serious, in order to be able to use such statistics in order to apply measures in the medium term, avoiding long term problems.
For this, we use python to study, collect and build the tool.
Hello, our team is Diego Seleguini, Gabriel Meneguini, Gabriel Valera, Lucas Bazan, Thiago Nogueira and Matheus do Prado, our team is special because we are concerned with how COVID-19 affects the food route.
Madlib: We need to analyze the food route to our home and how COVID-19 affects this, the people most affected are the lower middle classes of society, as the price of food has increased dramatically.
Expected Results + Data: we intend to help the population with food rationing, so that we do not suffer from long-term effects, about 73% of the Brazilian population is of lower class and would suffer a lot if they were not able to do it correctly, this not only for Brazil, but for the whole world, where we intend to arrive.
Ask: We intend to evolve the project, making the rationing calculation based on each country in the world, for that we will need specific data from each country, in order to conclude the final project.
We intend to use these resources made available by NASA, ESA and JAXA, in order to select the data and analyze it for study, in order to create a spreadsheet to use this information:
1- Collect important data;
2- Select what we could use in the tool;
3- Create a spreadsheet with tables and graphs for in-depth analysis;
4- Develop the prototype of the tool based on the data.