Inspiration
Our inspiration for Mindful Air was our desire to make a project that would have both a practical, yet unique purpose. After much brainstorming, we decided to tackle a project regarding the effects that air quality can have on a person's mental health.
What it does
First, Mindful Air gathers air quality data based on a location input from the user. After that, the app will take the user to a page that displays the levels of NO2, PM2.5, and PM10 in the location selected. Each of these pollutants have a unique affect on mental health when at unsafe levels. We compared each pollutant to the EPA's "safe levels," letting the user know if certain pollutants are at dangerous levels. Below the chart, we have specific facts regarding the affect each of the three pollutants has on mental health when at unsafe levels.
How we built it
We built Mindful Air using swift. Swift is an IOS app development language which we used on XCode, which is apples IDE.
Challenges we ran into
The biggest challenge that we ran into was converting JSON data into a usable swift structure. Although, our group had experience regarding API's, integration of API's using swift proved to be very difficult due to the modern complexity and concurrency aspects of the language. As a result, our initial plan of using API Ninja's Air Quality API failed as it seemed that no matter what we did, swift would not let us convert our JSON
Accomplishments that we're proud of
We are proud of making a functioning, clean, and good looking app despite non of our members having any experience in neither swift, nor app development.
What we learned
We learned a basic understand of the swift programming language, along with experience in Apple's IDE, XCode. Additionally, we learned many of the fundamental principles regarding app development and organization.
What's next for Mindful Air
The next steps for Mindful Air are to properly implement the Air Quality API and use it to provide data for any location. Additionally, we would like to provide better graphics and visual representations. Additionally, we could possibly integrate a automatic location detection system and a notification system.

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