Every species. Every site. Every day.

Watch live See the data

Today's broadcast.

Every bird that enters the frame gets a name, a timestamp, and the footage attached. The feed runs every day, dawn to dusk.

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Every visit. Logged.

Probability a species is present in any given hour.
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How this is measured

Live detector output. Each box, label, and confidence score is what the system writes to the public record.
BirdsUntold sensing pipeline Two parallel sensing tracks — a feeder camera feeding an object detector and species classifier, and a microphone feeding BirdNET — run on a single edge AI device. The two outputs are kept as separate logs: visits and calls. Every observation references source footage preserved on YouTube. Camera at the feeder Microphone alongside Carolina Wren · 0.91 feeder visitors trees overhead edge AI device object detector + species classifier BirdNET Cornell Lab Every visit. Logged. Every call. Heard. source footage preserved on YouTube
The two-track pipeline at a glance — visual and audio, kept separate, each linked back to footage.

A camera at the feeder runs object detection and a species classifier trained on North American birds, on a dedicated edge AI device. A microphone alongside it feeds audio into BirdNET — Cornell Lab's open-source sound classifier — so birds calling from the trees are captured too, not just visitors at the feeder. Audio identifications are logged separately from visits, and every observation has source footage in the full broadcast preserved on YouTube.

Origin · Beyond

My wife pulls up Birds of Virginia on her phone every time something new lands at the feeder. Nothing wrong with that. It just means for the few seconds the bird is actually there, we're looking at a screen instead of the bird.

So I built a camera that does the identifying. The system around it keeps doing it after we go inside. Dawn to dusk, every day. Species, time, duration, and the footage each ID came from. All of it kept.

— Anfon Ha · Lake Ridge, Virginia

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