Bird Detections
This page visualizes bird detections from my garden. The data is collected continuously by a small Raspberry Pi running BirdNET, which applies a machine-learning model to an audio stream and records detected species. Use the dashboard to explore which birds are active and how their activity changes over time.
Species images and image metadata are loaded from BirdNET Taxonomy; images without a clearly reusable license are omitted. Full software and data credits are listed in the Attribution section.
Species
Select the species shown in the dashboard. The tiles are sorted by activity in the selected time window; clicking a tile adds or removes that species from the charts and summary below.
Detection Activity
This plot shows how often the selected species were detected over time. Switch the time window above to compare recent activity with longer patterns, and use the species tiles to isolate individual calls or groups.
Daily Rhythm
This plot folds detections into a typical day. It makes morning, daytime, evening, and night activity visible for the currently selected species.
Species Summary
The table ranks the selected species by detections in the current time window. Species names link to eBird where a species code is available.
| Species | Detections | Last Seen | Share |
|---|
Attribution
This dashboard uses locally collected detections and builds on the following software and biodiversity data projects.
- BirdNET, an acoustic bird identification project by the K. Lisa Yang Center for Conservation Bioacoustics at Cornell and Chemnitz University of Technology.
- BirdNET-PiPy, the self-hosted BirdNET-based detection stack.
- BirdNET-Pi, the original Raspberry Pi BirdNET implementation that BirdNET-PiPy builds upon.
- BirdNET Taxonomy, used for species metadata, thumbnails, and image attribution metadata.
- eBird, used for species codes and species information links.
- Apache ECharts, used for the detection activity and daily rhythm plots.