DUI-Stopper

Preventing DUIs. Keeping you, your family and the streets safe!

INSPIRATION/PROBLEM:

To minimize the number people that are affected by alcohol impaired driving. Everyday, in the United States alone, there are 29 people that die from motor vehicle accidents that involve an alcohol-impaired driver, statistically standing to be one in every 50 minutes. We want that number to be 0! Our hopes and dreams are to have our software become a standard module that is included in every vehicle that is made.

WHAT DOES IT DO:

Identifies the location of the user and the proximity to public locations that serve alcohol, firing our application. The application then runs a module that tests reaction time and precision of the user to be fit to operate a vehicle safely. The user is given three tries to pass and after passing, the user is given the functionality to unlock their vehicle. Likewise, not passing the tests, the the user will not have that access and would be instead have the application contact an alternate form of transportation of their choice (as highlighted in the personal preferences). To prevent error, the user will be given the opportunity to unlock their car with three different passcodes.

BUSINESS MODEL:

License our software to car companies
Sell our product directly to consumers
Expand our functionality to remain competitive on the market

HOW WE BUILT IT:

Through blood, sweat and tears...and sleep deprivation
Sublime text editor for PHP and web development
Figma and photoshop for UI and concepts designs

CHALLENGES:

Merging code
Code compatibility
APIs available in certain languages
Diverse coding languages skills set of team

ACCOMPLISHMENTS:

Working with APIs and successfully implementing them into our project
Robust and dynamic back-end and front-end
Integration and compatibility between multiple languages
Fake machine learning
Able to control a car from the comfort of our seats

LEARNED:

About and how to use APIs
Code compatibility
The difficulties of merging Code
New languages
Sleep is vital
Difficulties and data hungry nature of machine learning

FEATURES TO HIGHLIGHT:

Google Maps API to identify bars and clubs that have the potential to suggest the driver may have drank alcohol or other substances of intoxication.
Voice analysis function with the use of machine learning to identify different speech patterns from the usual.
Game to test reaction time and precision that will act as the lock keeping the user from accessing their vehicle and instead contacts an alternate mode of transportation.

WHAT’S NEXT:

Integrating machine learning deep within our platform to learn from the user data that is gathered for negative behaviors and pattern discovery and warn the user of it.
Voice analysis using machine learning to determine whether the user is drunk