Struikgewas hears what
sounds low.
The microphones hang on the shed in the garden, sheltered from the rain under the gutter. At shrub and garden height they pick up what moves close by: dunnocks slipping through the bushes, wrens that suddenly belt out a loud song from nowhere, robins marking their territory. But these microphones also catch what passes overhead pretty well.
About the confidence score
An algorithm is no ornithologist
Every detection comes with a confidence score. 92% chance it's a blackbird, 23% chance it's a noctule. The number looks scientific, but it remains a model's guess. Often very good. Sometimes completely off.
A few from this garden. A bicycle bell once became a bullfinch. A bouncing ball down the street, an eider. One pipistrelle sounds almost identical to another, as far as BatDetect2 is concerned. The algorithm misfires there regularly, even at 95%. Rare species are extra suspect. The model has seen fewer of them, so a detection like that stands on shaky ground.
I check the less common and rare species myself. For each detection I play the recording back and see if it holds up. But that leaves me running behind sometimes. I might only get to it days later, and until then a doubtful case just sits on the site.
So those numbers are a hint, not an identification. An algorithm that listens day and night hears more than I ever could on my own, and that's already something.
Just in.
Every detection from BirdNET-Pi berging shows up here straight away. The microphone hangs low. So what you see here is mostly callers and begging youngsters, no fly-overs.
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Listening.
No detections since you opened this page. A quiet stretch means nothing was heard, not that the pipeline is down.
Birds don't just sing. They call, alarm and make contact sounds.
Custom CNN models decide per detection whether it's song, call, alarm or something else. Counts over the last seven days, for the top 10 most-heard species.
| Species | song | call | alarm | other |
|---|---|---|---|---|
| Common swift | 6,489 | 4,546 | 8 | 1,569 |
| Common blackbird | 5,671 | 2,586 | 260 | 2,234 |
| Eurasian collared dove | 66 | 1,322 | 49 | 280 |
| Common wood pigeon | 474 | 885 | 109 | 245 |
| Great tit | 603 | 399 | 157 | 238 |
| Western jackdaw | 401 | 567 | 99 | 209 |
| Eurasian magpie | 396 | 134 | 406 | 162 |
| Eurasian blue tit | 65 | 578 | 111 | 232 |
| Common chaffinch | 106 | 188 | 205 | 102 |
| European greenfinch | 54 | 150 | 77 | 110 |
Song = territorial (song / subsong / display song). Call = communication (call / begging call / flight call / nocturnal migration call). Alarm = predator spotted. Other = raw drumming or unclassified by the model.
What there was to hear low down.
The low shrub layer mostly captures callers and begging youngsters. A script picks the three clearest recordings of the past year per species, every night.
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Alle soorten bekijken →The classics.
Rarities, one-off passers-by, and moments I don't want to forget myself. Every single one fished out of the archive by hand.
No highlights marked yet. Ronny regularly picks new ones.
- Today 1 different species, with a total of 16 detections.
- Peak today around 00:00 (16 detections). The 30-day average peaks around 05:00.
- Today fewer detections than the average over the last thirty days (-100%).
Struikgewas runs on a Raspberry Pi 5 (8GB) in a weatherproof enclosure on the shed in the garden. Two microphones hang under the gutter of the shed, sheltered from the rain, at shrub height. The Steinberg UR44 audio interface handles the input. BirdNET-Pi analyses every three seconds, and then the same CNN models as on Bladerdak determine the vocalisation type (song, call, alarm or contact). North/south direction detection doesn't work here yet. That'll come later.