UFAir has received the following awards and nominations. Way to go!
UFAir is a web app that relates and shows connections between different datasets involving pollutent gases presents in the atmosphere and diseases as well. The interface was designed to maximize accessibility and confort, so anyone can manipulate with ease difficult data analysis, such as heat maps and correlation matrices.
Researches have shown that air pollution causes millions of deaths every year. Our actions in everyday life affects the atmosphere's composition locally and globally, but most of the time this relationship isn't clear which fogs the big picture. Population's awareness of these factors are essential in order to prevent the situation from getting worse.
The site can be accessed from any browser at the link https://ufair.herokuapp.com/. In the plataform the user can choose which parameters to compare (Pollutent gases, diseases, COVID-19 cases, etc), and also one of the following visualizations:
Then, it's possible to see how these parameters and analisys changes over the years, controling de time of observation using the timeline presented at the bottom of the page. As part of our future plans, this timeline also can be set to future days, in which the plataform will calculate possible outcomes for the current situation.
We hope that this tool succeds in helping people to understand how the Earth's atmosphere is changing and in which way does our day-to-day lifes are influencing this. With awareness and a better comprehension of these phenomena, we can hope for a more sustainable and healthier future.
UFAir was developed using Python with the Streamlit framework. The choice of framework and programming language was based on efficiency for processing big amounts of data and responsiveness for the user in the front-end.
The datasets for air polluntents and public health used in the plataform are available free online, provided and updated by National Aeronautics and Space Administration (NASA) and World Health Organization (WHO) .
Our team faced a lot of challenges on the way, but succeded in a very constrict time schedule, we were able to research, organize, learn e utilize a wide range of information and tools to develop a project and present it.
Sattelites' data are a very important part of the process of information parsing at the project. UFAir uses CSA's datasets in .csv format, to collect CO2, NO2, CH4 and O3 amounts over the world, from years 2004 to 2020. The information of date/time, geographical coordinates and mean amount of gases are extremely useful for analysis' sake.
Prototype: https://ufair.herokuapp.com/
Extra analysis: https://colab.research.google.com/drive/17e8KUz5nIRovjRh4-zB1Gz275-voeqnS?usp=sharing
Presentation video: https://www.youtube.com/watch?v=kTK2PbgTeLg
Presentation slide: https://drive.google.com/file/d/158frJwWoDjeC9rnzoKyIKsU8C3Kq9rw-/view?usp=sharing
OMS data: https://covid19.who.int/
CSA data: https://www.asc-csa.gc.ca/eng/open-data/access-the-data.asp
SARS data: https://www.kaggle.com/imdevskp/sars-outbreak-2003-complete-dataset
MERS data: https://www.kaggle.com/imdevskp/mers-outbreak-dataset-20122019
H1N1 data: https://www.kaggle.com/imdevskp/h1n1-swine-flu-2009-pandemic-dataset
Global air pollution data: https://www.kaggle.com/kweinmeister/pm25-global-air-pollution-20102017