According to a study done across 1.8 million past emergency service calls, the average response time was 14 minutes. In situations where the difference between life and death can be a mere second, we recognize it would be in the best interest of society as a whole if we could allocate the most time possible, to the people who need it most, when they need it most.
What it does
Utilizes machine learning and a serverless infrastructure to streamline the emergency services calling process so that emergency services can get where they need to be and provide assistance as fast as possible.
How we built it
HTML/CSS/Ember.js, Serverless, Python, Machine Learning, NLP, AWS Lambda, Twilio API
Challenges we ran into
Getting the Twilio API to function as intended (inbound call receiving, call recording, etc)
Accomplishments that we're proud of
All the progress we made in such a short timeframe.
What we learned