High-Level Project Summary
Co-vision is programmed by "Android Studio." Our app is a built-in map that shows the users any nearby suspect of the virus by using marks on the map. These marks are of different colors; the red ones represent an infected person, while the orange ones represent suspects. All of these data are stored anonymously to assure the users' privacy.By showing all the users all the data needed for them to identify the danger and avoid it, knowing information like these will increase people's awareness and sustain the health security of the countries. All of that will leave us with a world of highly aware people that can then cooperate to decrease the number of cases and increase public health.
Link to Project "Demo"
Link to Final Project
Detailed Project Description
First of all, when the user first joins, personal data is collected, for example, name, age, e-mail. After the user logs in to the app, the home page will be a map that shows every infected and suspected user currently using the app; they appear in two different colors and are completely anonymous. The first color is red, as any red mark on the map will refer to an infected person. In contrast, the second orange will refer to a suspected person that any user has to keep their precaution measures by wearing a mask and applying sanitizers. Avoiding the whole area marked red would be a great first choice, but considering the precautions will be very important if necessary. Co-vision stores all the coordinates that every user has been through over the last ten days in a database. These coordinates gave us a colossal feature that alerts people if they have been in contact through the coordinates with anyone that recently discovered the covid infection. The app will then suggest either testing for covid to ensure that the person in touch did not get infected or self-isolated for nine days. This alert will ensure that even if they carry the virus, they won't infect anybody else.
The app collects the data of the infected people in 2 ways; the first one is by cooperating with the health ministry to keep up with any new signed case. The second is by filling a survey that the app will display; this survey will be of some questions that will confirm either the user is a suspect or not. The survey will also ask about any exceptional specific medical condition or any chronic disease. To ensure that the infected will fill this survey, we had to make a reward system that will ensure that most of the cases will fill this survey, which will be developed by machine learning to give more accurate results and health tips. Co-vision updates its users with the newest issues, cures, and deaths using the dashboard by CSSE at JHU.
The app benefits many people in different ways. The user, for example, who admits the infection will be rewarded; this reward can be in the shape of discounts on some health stores or by paying fewer taxes for the government for a certain amount of time. Also, the map will show the nearest places from the user's current location to vaccinate. As for the CSR of our app, by applying this reward system, more covid cases will show up, and by cooperating with the health ministry, we can share the data of the new patients, which will be a great point in our society. All of that will increase the awareness of people. People don't usually realize the surrounding danger, but with Co-vision showing where to go and what to avoid, health safety will increase, and people's mindsets will change about pandemics. This will have a significant impact in the future while facing any new sort of pandemics.
We are hoping that our app will be a significant part of raising the awareness of humanity, which will decrease the number of cases, hoping for covid to come to an end. We believe that the idea of our app can change the world in the future since people will be aware of any new diseases. This will achieve our hope in a peaceful, pandemic-free world.
We used "fire-base" to store Co-vision's data, "android studio" to program the app, "Java" and "XML" as coding languages, and "Android-Studio's emulator" and our phones to test the code.
Space Agency Data
We used the Centers for Disease Control (CDC) data to know the exact symptoms of covid-19 and when somebody will need medical care, which will help when using machine learning and to ensure public health safety.
The data from the Covid-19 dashboard by the center for systems science and engineering (CSSE) at John Hopkins University (JHU) keeps the users up to date with the latest news about cases globally or nationally.
The EO dashboard will be used to track the progress of our solution by showing charts of the new cases.
Hackathon Journey
Our team is utterly new to hackathons, so Space Apps is our first hackathon to attend, and unfortunately, the hackathon is online, so we had to deal with some problems. The whole experience was new to us, but we found it very beneficial because we learned more about problem-solving and how to face setbacks and dead ends. Also, we got a lot of information while trying to solve the problems that faced us, either technically or practically.
While surfing through the challenges, our eyes fell on this challenge; and we realized that our lives had taken a significant turn since Covid spread, which changed a lot of our lives. Because of the quarantine, many people lost their jobs and ways of income. While on the other hand, some people were mentally affected by staying at home for too long. So, we hoped that we could make a difference and benefit our world with our idea.
When a problem faced us, we would all join an online meeting and brainstorm together. All of us would say our ideas even if they were not applicable, and then we would look together through all the solutions and figure out a way to solve the problem. For example, when we were thinking about the idea of the app, we faced a problem with the database since we couldn't afford one. Also, none of us knew how to use SQL, so it was impossible to create our database. That led us to search more and more until we found online databases that we used in our prototype.
We want to thank our great mentor Karim Nabil who helped us through the hackathon; whenever a problem faced us, he told us some suggestions on how to solve it, joined many meetings, and guided us to know what to do. He also was a huge supporter since he told us how much he liked our ideas and work.
References
Source 1&2: Both sources were used to keep the user updated with all the information about new covid cases.
Coronavirus COVID-19 (2019-nCoV) (arcgis.com)
https://gisanddata.maps.arcgis.com/apps/dashboards/bda7594740fd40299423467b48e9ecf6
Source 3: Used to track our progress by showing charts with different times and numbers of cases.
https://eodashboard.org/?poi=W6-NASAPopulation&country=EG
Source 4: Used to get all of the information about symptoms of covid.
https://www.cdc.gov/
Source 5: Used to program the whole application
https://developer.android.com/studio?gclid=CjwKCAjwhuCKBhADEiwA1HegOXUv2hWnZ2lzi4WeGN5yI2HYWR2evfBg3VcQ2sgfT_x6jUZHCl_91RoC63cQAvD_BwE&gclsrc=aw.ds
Source 6: A Java tutorial.
https://youtu.be/eIrMbAQSU34
Source 7: Android studio tutorial.
https://developer.android.com/courses/fundamentals-training/toc-v2
Tags
#covid-19 #covid-calculator #case-rates #death-rates #android-studio #data-base #awareness #health-security #git-hub
Global Judging
This project has been submitted for consideration during the Judging process.