Inspiration

Our close friend's grandma was diagnosed with dementia and through him, we learned of the hard times when she was unable to think of the right words to express herself.

What it does

Our app is unlike anything you've seen before. It solves one of the biggest problems that people suffering from memory loss. There have been many attempts to solve this problem, such as constant reminders and pacemakers, but none of these have been shown to be effective. Even doctors recommend that patients should sit with their eyes closed and think about their pasts. This may be easy for the doctor to state but for a struggling victim, it's much more than just that. Our app uses facial recognition to identify the victim's family and friends. This allows them to seamlessly interact socially without the need to be mortified.

How we built it

We built this app using Android-Studio 3.0. Specifically, we incorporated Java and C to build a platform for our app. Additionally, we had to look into quite a few different APIs in order to achieve the facial recognition we started out with. After figuring out an API that would be able to recognize a human face given a series of photos, we were able to combine it with our user interface to produce Face2Base, a name representing how a face can be recognized from a database of photos.

Challenges we ran into

The hardest challenge we went through was figuring out the facial recognition. It was difficult to find a proper API that we would be able to use and implement. Our initial idea was to build an app that recognizes people. After completing hours of research for APIs, we were unable to find one that we knew how to use. Most of them used C, which none of us knew how to do. After hitting this iceberg, we decided to stick to just face detection. This meant the app would let people know when a face was detected. We were not fulfilled with this and decided to switch back to face recognition.

Accomplishments that we're proud of

After completing this project, we were extremely proud of ourselves. We had learned to code in C and get past the fact that we would be using an API that was unfamiliar to us. We had also learned to code a facial recognition application. These types of apps would usually take days to code, but we were able to work together an do the best we could in just 24 hours.

What we learned

After these extremely enjoyable and educational 24 hours, we learned how to make a facial recognition app and use APIs that use C, which none of us knew until coming to this hack-a-thon.

What's next for Face2Base

We hope that we can provide this app to neighborhood doctors and medical practitioners. This would allow us to spread our app to the market that we are targetting. We also would like to add an audio option for vision-impaired people. Hopefully, people diagnosed with this condition will be able to communicate the same way they did before, thus helping them connect and build relationships that are necessary for life

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