facialCheckIn

Inspiration

We wanted to offer something new and practical to optimize the experience of boarding a flight for both the customer, as well as the employees, specifically the gate agents.

What it does

A customer's picture carries the same information that their ticket would carry, such as their name, flight, and priority level. An employee logs into our app and every picture they take of a customer will return their information. It speeds up the process of getting a flight. In addition to that, we also accounted for overbooking situations by listing every low priority level customer per flight. We use a last in first out sort list so should there be an x amount of high priority level customers without a seat, we remove the last checked in low priority level customers for the flight, and store those in a list to be reassigned to another flight.

How we built it

We built the app using Android Studio and wrote with Java and Kotlin. The facial recognition feature was implemented using Microsoft Azure's facial recognition software (Face API).

Challenges we ran into

We initially planned to just implement algorithms to expedite the gate keeper and bag handler's jobs, but we decided to abort that and try something new, as we figured there is already something in place to satisfy that. We changed our overall project about 10 hours in and had to work faster than we'd plan to.

Accomplishments that we're proud of

Definitely the facial recognition software as pictures taken are matched to our database of photos.

What we learned

Got familiarized with Azure Face API which can definitely be used for other projects.

What's next for facialCheckIn

Should it be deemed practical by Southwest Airlines, we would like to begin implementing this in airlines to speed up the check in processes that are currently in place.