Dr. Coronata

Form for anonymous dataset insertion.
The corresponding heatmap that will be generated by the server
Heatmap with bigger centers of infections

Mission

We enable the best local Corona avoidance map for old and young communities. Our goal is to track minor and major symptoms of people to determine early centres of infections.

Inspiration

The corona virus pandemic is spreading fast, hospitals are fighting for resources to help every newly arriving patient and economics are breaking down slow and steady. Under these circumstances, we have to work together as a local and global community where everyone must do their part to minimize the extent of the virus.

Dr. Coronata helps people and institutes with this task by offering an individual health check on the symptoms of the corona virus and by providing a heatmap which illustrates individual risk of being infected based on your health and living area. Therefore, People can use the App to avoid high infected areas and minimize the risk of being infected. Institutions can use the App to detect early infection rises and effectively manage their financial resources to support heavily affected areas. Hospitals can prepare themselves with a higher capacity in specific areas to keep the mortality low.

What it does

The user will do a quick health check which are fed into the system as anonymous data e.g. gender, age, preconditions and symptoms (e.g. picture 1). This dataset will be sent to the server to populate a heatmap (picture 2) based on your individual infection risk. The heatmap operates on a global and local area which is a task other heatmaps fail to solve.

How we built it

Our backend consists of our own database (postgreSQL) that will save the needed data for incoming datasets. This database is connected to our REST-Server to interact between database and app. New heatmaps will be generated periodically at the REST-Server and will be sent to the corresponding client.

Challenges we ran into

The most problems occurred at setting up the needed infrastructure. These were small but took a chunk of time here and there (e.g. setting up the database for public use, buggy module installations). Some problems were related to a lack of knowledge in Xamarin programming. This was learned successfully during the process.

Accomplishments that we are proud of

In under 48 hours we made a successful prototype through permanent communication and help between each team member. This couldn't be done without proper teamwork.

What we learned

~Communication and organisation are key.

What's next for Dr. Coronata

GPS tells you which areas you want to visit have a high infection risk and the app offers you saver alternatives
Publish the data to predict new centers of infections (Machine Learning)
Enhance the statistical possibilities (Big Data)
Insert new Corona cases explicitly into the database to improve the value of the heatmap
With activated GPS, push notifications will alarm you if you are in a high infectious place.