No one likes waiting in line. Especially when checking into an event or meeting, lines are slow, inefficient, and detracts from the quality of the event. CheckN is here to help save your time so you can focus on what matters. We make this process easy for everybody, including those with disabilities.

Inspiration

We are all heavily involved with ACM and ACM-W events on campus. We noticed it takes a good amount of meeting time to check people in, usually by having them fill in a Google Form or Excel Sheet. Most of the people attending are regulars, filling in the same information and holding up the line for newcomers. How could we make this process faster?

What it does

CheckN is an android app that will allow users to check into events with Microsoft Face Regocnition. After taking a photo of someone's face as they enter the event, our app will scan a database of users. If the person has shown up at our events before, we have them already saved in our database. Done! They are checked into the event. If we have a new face, adding a new user is fast and easy. Seeing them at future events will be even faster!

How we built it

We used Microsoft Services Cognitive API, to do facial recognition. This involved training models of people's faces. User history would be saved in a JSON file. On the Android application, we call various endpoints of the Face API. We used Android Studio to create the app using several libraries including Butterknife to bind views and Google's Gson library to serialize and deserialize JSON files. We made a python backend that (ideally) that would also update the checked-in user on the event details. In this, we used the Twilio API to send a text message to the user. Event details would also be given in a JSON file. We also created a universal Windows application that can access the webcam.

Challenges we ran into

  • This is our first time working with Microsoft Cognitive Services
  • We weren't able to make a cloud database to hold our history and files, however, it works quite well on the native app. This was going to connect the JSON to each element of our design to interact with each other.

Accomplishments that we're proud of

  • Being able to use Cognitive API!
  • Coding in python to call Twilio API!
  • First time python users! (2/4 members)

What we learned

What's next for CheckN

  • Making an admin userface for business, clubs, and event coordinators to have their own personal databases.
  • Adding in voice feedback so people with disabilities (blindness, age, arthritis, ect.) can still check in with ease using a receptionist interface.

Built With

  • java
  • python
  • microsoft-cognitive-services
  • microsoft-face-api
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