What it does
Differentiate between drone types.
How we built it
Using python and catboost library.
Challenges we ran into
Making a good quality model with low resources.
Accomplishments that we're proud of
Making a working AI.
What we learned
Catboost and AI in general.
What's next for DroneSniffers
- Future Implementation: The two nodes work independently, the Sniffer runs continuously, then once a drone is detected, it sends an API call to the Brain node. This saves resources as the Brain Node won’t always be loaded and ready.
- Integrate DroneSnifferLive; a program that actively searches for drone audio with the use of a microphone, when a potential drone is detecting and confirmed, the DroneSniffer (primiary program) identifies and classifies the drone based on the collected acousitc data
Built With
- catboost
- python
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