We were inspired to implement this idea since it could help the university become safer with students back. We want the freshman and sophomores in college to be able to get back to normal as quickly as possible so they can have wonderful college years -pandemic free. Colleges present many unique and exciting opportunities for not only students, but also the communities surrounding campus. Keeping campus healthy doesn't just help schools, but the entire community.
We have never coded in the dart language or used any of the google products that we used here so it was a big learning curve, but worth it. We were able to work as a team, learn many new valuable skills, and code a really hard topic with a significant cultural impact on today's world.
The guiding principle was fairly simple: as students went about their day on campus, their smartphones send out a hashed value (based on their student ID) over blue tooth. Every time the student is in close proximity with someone also using the app, the two signals ping off the devices, and the event is logged. If a student tests positive, a healthcare professional inputs it the system, associated with the student's ID number. Once a positive test was logged, the system performs a search query for all events involving that hash code over the previous two weeks. Then we'd like to use FireBase ML models to assign a risk associated with that contact event. Then the system sends our messages to people who have been in contact with a positive case, tailored to the level of risk associated with that contact. Where our system truly sets itself apart is in utilizing campus infrastructure such as key swipes to log events. Having a more centralized (but still secure) data structure allows for healthcare and university administrators to view a dashboard of trends and insights into where outbreaks may be at risk of occurring.
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