The Sound of Sirens

Inspiration

A post on DevRant by a hearing impaired developer who describes the impact of technology and automation in improving quality of life for individuals with disabilities

What it does

A wristband that detects sirens in real time, and alerts the wearer of their presence. The target audience is hearing impaired individuals who drive.

How we built it

We use the Urban Sound Dataset to train a neural network to recognize the sound of sirens. The application then signals the Myo wristband which vibrates to alert the wearer. We used Python bindings for the Myo SDK.

Challenges we ran into

Improving model performance, working with corrupt data, microphone issues, training in AWS, attempting to port application to Android

Accomplishments that we're proud of

Getting a prototype working; understanding how neural networks work as beginners to machine learning;

What we learned

Interfacing with software. AWS

What's next for Siren Detector

Move all functionality to a smart watch; extend to detect other life threatening sounds like gunshots, trucks backing up, fire alarms, etc.

Built With

Submitted to

HackUMass V

Created by

I worked on the early Myo integration in python as well as refining the data set that the neural network used to train.

Robin Yu
I worked on refining the data set and building the neural network.

Akshay Ravichandran
I worked on building the neural network model and improving prediction performance

Ananya Ganesh
Liam Britt
CS student at Umass Amherst. Interested in helping people through health hacks and solving cool problems.
Jason Valladares

Updates

Liam Britt started this project — Nov 05, 2017 08:43 AM EST

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