After seeing first-hand people
What it does
SafetyNet is an app that allows people with the right skills and certifications, willing to help in over-crowded emergency situations. Medics, Certified First Responders, Certified Technicians.
How I built it
We did an exhaustive research on the emergency response sector, from interviewing Emergency Dispatchers, Certified First Responders, and Medics to watching and reading of their everyday jobs and responsabilities. We created an application that utilizes IBM Watsons natural language processing and converts speech into text for the dispatcher and responders to see. Server calls were made using Node.js. We also used Mapbox API to render a map the map view.
Challenges I ran into
Was really hard to find a team to work with. I met Motorin, my teammate when she got into the building at 2 am. We frequent ran into the issue of getting the API to work. We pivoted multiple times after a while working on the product and better understanding it cause of the type of problem we targeted.
We frequent ran into the issue of getting our NLP run properly, we were particularly interested in using the Google Cloud because of it’s capability to consider context and sentiment, but ultimately used IBM Watson in the interest of time. (edited)
Accomplishments that I'm proud of
After all this research we could gather data that was useful. Worked on IBM Watson for the first time. None of us in Computer Science major or have a strong background in development. Medina is a Designer major and Motorin is a Business major.
What I learned
How inefficient a core service like 911 could be nowadays. 1 out of every 5 cases the US 911 system can't accurately know where the
What's next for SafetyNet
Using a natural Language Processing Model to gather and work passively on the Dispatcher's side. Using sentiment analysis, data gathering, context, and language location. Better use of Mapbox and create a React Native mobile app.