Alcohol-related injuries is one the three most common deaths in young adults. Studies of adolescents show that heavy and extended alcohol use is associated with a 10 per cent reduction in the size of the hippocampus, the part of the brain responsible for memory and learning, and prefrontal lobe which is important for planning, judgement, decision making. To combat these health risks, we created a solution that will promote responsible alcohol consumption and aim to decrease the number of drunk drivers.
What it does
BoozeBuddy is an Apple watch application that notifies users of current BAC, sends vibration notifications as a user gets close to an unsafe drinking limit, and provides functionality to call RideShare Services.
How I built it
We used a machine learning model to determine when the user to taking a shot of alcohol. For the Apple Watch Application, we used Swift and XCode.
Challenges I ran into
The documentation for Apple Watch was very little so development for the application was slow. Since our data was sequential, we decided to use a Recurrent Neural Network but it was hard for use to implement because we were new to it.
Accomplishments that I'm proud of
We were thankful to get a fully functional Apple Watch Application that keeps track of the number of drinks a user has drunk.
What I learned
All of us were new to Apple Watch and mostly iOS Development.
What's next for BoozeBuddy
We're passionate about the idea of BoozeBuddy and would like to keep building it out. Some features that we would like to implement are connecting the Apple Watch with RideShare and Emergency contacts and implement more animations for the application.