Shazam 4 Drones - BBUAV

• 

  Dashboard

Inspiration

We were inspired by the idea of creating a “Shazam for drones” — a tool that can listen to audio and instantly recognize whether a drone is present.

What it does

Our platform detects drones from audio recordings:

• Users can upload .wav or .mp3 files through a clean Next.js frontend.

• The backend (FastAPI) processes the audio, extracts MFCC features, and runs them through a trained Random Forest model.

• The system returns a prediction: which drone type (or “no drone”) was detected, along with a confidence score.

• Sends live alerts using Twilio to your phone or email.

How we built it

We built a React + NextJS app that works with a RF classifier model in the backend using FastAPI and that sends SMS alerts via Twilio

Challenges we ran into

Time as always

What's next for Shazam 4 Drones - BBUAV

Make the platform work for live audio!

Built With

• fastapi
• next
• oauth
• react
• scipy
• sklearn
• twilio