Using the SEDAC’s Population Density Map and Johns Hopkins University’s COVID-19 data, we’ll create an application that uses information collected from both databases and combine these to provide a map with population density and number of cases around the user’s location and other places all over the world.
The application will use the GPS of the mobile device to indicate the position in which the individual is located and he will be notified by the application if he is in a place with a high or low degree of danger of contagion, based on the population density and the number of cases of Covid-19.
Besides, the application will be able to show the statistics of the increase of infected, dead, and people in a state of possible contagion by COVID-19 in a specific area. (*the pattern of increase of COVID-19 can be seen).
The users of this application will have the possibility to indicate points where there is a high concentration of people and the platform will use this information to update it’s data and notify the surrounding users that there is a high probability of contagion on that place. Also, the application will display notifications in the form of tips, for example: "Smoking makes you a high-risk’s objective of COVID-19", "Remember to wear a mask when leaving home", among others.
The application will also be able to predict the possibility of an increase of cases in a city, making use of an AI that analyzes the cities close to the users, in the same way, it observes, if any of those cities have a high percentage of COVID-19 infections, if so, it will notify the citizens, so that they can take extreme prevention measures because of the probability of an increase of infections.
We use the data from the spacial agency in the following way:
SEDAC map: https://sedac.ciesin.columbia.edu/mapping/popest/gpw-v4/
GitHub repository: https://github.com/CSSEGISandData/COVID-19
We used the SEDAC map as a basis for our project since it provides us with different views (Road, Air, Country, and Topographic Maps), but the main reason we chose this map as a basis, is because it has the characteristic of showing the population density, which was necessary to solve the HUMAN FACTORS challenge, then we used the ".CSV" files that Johns Hopkins University uploads daily to its GitHub repository, each of these files contains diverse data about COVID-19 cases from different regions of the world and the most important thing about these files is that they have the latitude and longitude coordinates of the location of the contagion cases, which allows us through a script to read, analyze and place that information about the SEDAC map using the coordinates obtained from the ".CSV" to accurately place the University's information on the map, thus creating a new more complete map. Also, we use a small artificial intelligence that, based on the data from Johns Hopkins University and the population density of the SEDAC map, allows us to predict which city or place the COVID-19 could expand and thus notify users to take precautionary measures.
Our inspiration for this challenge was:
The human factors issue caught our interest since COVID-19 started as a simple outbreak in Wuhan City on December 1, 2019, to be considered a pandemic on March 11, 2020 and everything falls on human behavior to overcome this crisis.
Through this project we seek to raise awareness and inform about the virus in a simple way through our application. We offer real-time information about the virus and it’s trajectory, as well offering advice, strategies and ways to safeguard our health in these times of need. We see this application, not only as an informative app, but also to educate and make users aware of how our actions can be a positive contribution to overcome this crisis.
To develop this project we focus on:
We focus directly on the reasons why this virus spread was so rapidly on different continents, analyzing different regionalized human factors. Among the reasons that stood out the most for our interest were economic, social, cultural, hygienic and psychological, to find quantitative and qualitative factors that may be necessary for our study.
The tools, software and hardware we use to develop our project are the following:
Here's a video of our project:
https://www.youtube.com/watch?v=Nw6J_mJ2Mm4
:D
And here's the prototipe of the app (only demo has no functionality) :D
Blumenfeld, J. (23 de April de 2020). NASA SEDAC Application Puts Current Global COVID-19 Data at your Fingertips. Obtained from https://earthdata.nasa.gov/learn/articles/sedac-covid-19-viewer
Johns Hopkins University. (2020). COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE). Obtained from https://github.com/CSSEGISandData/COVID-19
NASA: EARTHDATA. (2020). Global COVID-19 Viewer. Obtained from https://sedac.ciesin.columbia.edu/mapping/popest/covid-19/
NASA: EarthData. (2020). Global Density Viewer. Obtained from https://sedac.ciesin.columbia.edu/mapping/popest/gpw-v4/