Our project is focused on using facial recognition to match photos taken by a user to a database of missing children, to aid law enforcement in finding them and getting them to safety. The application is an IOS app, making it portable and easy to use.


Rates of missing children are rising at an alarming rate. As a result, the exploitation and sex trafficking had risen as well, with over 10,000 exploitation cases in the US reported in 2017 alone.

What it does:

Our project matches the photo that the user has taken to a database of missing people.

How we built it:

We built our project using swift and APIs with along with a data scraping program. Xcode was the application used to build the majority of our project.

Challenges we ran into:

Challenges that we faced included a steep learning curve for Xcode and the language Swift. Only Grace had experience with the two and there's usually not two different things to learn in the same weekend).

Accomplishments that we're proud of:

We are able to make a data-scraper along with configuring the Waston API to our application for facial recognition.

What we learned:

Xcode, Watson Visual Recognition API, Core ML, Swift

What's next:

We will further develop it and add more features along with better graphics.

Built with:

Xcode, python, along with multiple other programs.

Prizes we're going for:

Intel® Movidius™ Neural Compute Stick

TBI Pro Gaming Headset

$100 Amazon Gift Cards

Social Entrepreneurship Award

Hustle Award

Grand Prize

Blu R2 Plus Smartphones

Misfit Shine 2

Raspberry Pi Arcade Gaming Kit

Team Members

Grace Hall, Arta Razavi, Cameron Harvey, Lynn Li, Andreya Augst
View on Github