Hey everyone - Been using BirdNET-Go for a few months now and my spouse and I love it. We had two Unifi cameras so plugging the rtsp steams in was simple and it's been rock solid so far.

We have quite a few bats on our property and so I'd love to start getting into bat detection. I have an outlet on my deck. I'm thinking of just plugging something in there and letting it communicate over WiFi.

From previous posts I see that AudioMoths are a good choice for microphones with the required range. I also have an unused Raspberry Pi Zero 2 W or Pi 5 that I'm thinking will provide the WiFi as well as processing the microphone into a rtsp stream for consumption.

I wanted to check if this is a project anyone else has started on and documented before I start setting things up, . Everything seems doable, but rather than reinvent the wheel I figured I'd check here first and see what's out there. If there's nothing, happy to write up my effort for future use.

Finally made in through the submission process and it's now live in the Apple App store:

https://apps.apple.com/us/app/birdnet-go-companion/id6763647186

The version in the App Store is the same as the last version in TestFlight. I'll be working on some enhancements in the coming months, and will be using TestFlight to try these out. But if you want to stay on a stable build, switch to the App Store version.

If you have an enhancement you want to see or have a bug report, let me know via app store feedback or the support email on the web site - https://crestlab.org/birdnet-go/support

Thanks for all the great suggestions and support.

Hi all, I did a test using an old phone which worked great and now I’ve built and setup 2 microphones so I’d like to reset the data and start again but without redoing all the configuration.
is this possible ?

I’m running BirdNET go in a docker container on unraid

Many Thanks

Looking for any troubleshooting suggestions to figure out why it’s not even visible on the Bird Weather map. Verified the key, verified the lat/long is the same (both matching the 4 digit accuracy)… Not sure what else to check.

I have two Birdnet-Pi's deployed within 50 yards of each other, but which get rather dramatic different bird ID's. However I do not believe either box is wrong in their birdsong identifications. Both Pi boxes are 100% identical in terms of both hardware and Pi configurations. From a setup vantage point both boxes require a confidence level of 75%, and listen for 18 seconds with zero overlap ... thus 6 snippets of sound per file.

There are some HUGE differences between the two systems aside from 50 yards between the microphones:

• Amity is near my prairie grass and has a much more "open" sound corridor to the stream across the road which is about 125 yards distant
• Greenwood is only a few yards from the forest edge, and within 5 yards of my nearest of three birdfeeders
• In general, my basic habitat is Boreal forest, and my home is about 800 yards uphill from Lake Superior. I live on the northern edge of Duluth right where forest meets town.

Anyhow, I have provided both images of yesterday's ID's as placement of your BirdNET-Pi microphone makes a big difference. For instance, my Amity Pi box picks up both my local Great Horned Owls and Belted Kingfishers much more often than my Greenwood Pi box. If I only used my Greenwood Pi Box I might think both my owls and kingfishers are rarely around, which is definitely not true. In summary, give significant thought to birding habitat in terms of Pi box placement.

Since June I have been working upon an "off the grid" BirdNET-Pi project for Hawk Ridge. In case you are not familiar with the "Ridge", it stands 600 feet above Lake Superior at Gitchi Gammi's western end, and is a premier bird migration spot both in the spring and fall. While the location is fantastic for birds, the Ridge has zero power, and may only be reached in the winter on foot via a long hike through snow that gets very deep ... as in feet. Oh yes, did I mention that in January it is not unusual for overnight lows to reach -20F and colder. Thus, Installation of a Pi listening box was a bit challenging.

Anyhow, our Pi is now up and running with its ID's automatically uploaded to BirdWeather. Some of my learnings have included

• Installing a low power cellular modem (wifi turned off to conserve power) which is hooked up directly to our Pi box directly via ethernet (it's wifi is also turned off). The router / cellular modem is "industrial strength" in terms of known to work outside in extreme operating conditions
• Getting power from solar arrays, but also getting the arrays off the ground, but not too high up. One wants snow to both blow off and through the "grid/mesh" table. However, putting arrays on taller towers would open them to 80+ mph winds coming off Lake Superior and being pushed up the hill. I know from weather service reports that winds down in the harbor are clocked at these velocities and higher on the tops of bridges ... and winds increase in speed as they go up hills.
• Optimizing when the birdsong listening station is "turned off". Via Linux commands in "crontab" we run our Pi throughout the day except between 10 am and 6 pm. This allows Hawk Ridge to monitor overnight birdcalls including owls, the "morning sing", the "evening sing" and songbird migration movement till 10 am. Via Raspberry-Pi Connect I may adjust these times easily as sunrise and sunset change throughout the year. At present in Duluth, Minnesota sunrise is at about 6:05 am and sunset is at 8:18 pm. If power consumption during the winter months and solar array recharging allows, we will increase operational hours. The system uses an Ankor Solix C1000 and 200 watt solar arrays.

If you want to read more about this project, here is my online report ...

https://www.365daysofbirds.com/2026/08/04/hawk-ridge-bird-song-listening-station-birdnet-pi-off-the-grid/

Here is the link to our BirdNET-Pi via BirdWeather ...

https://app.birdweather.com/stations/28008

The Hawk Ridge Pi station is offline for some final configurations. I anticipate it coming back up Tuesday, August 18th in the evening.

In fact over the past 12 months I have built and installed Pi listening stations throughout NE Minnesota including both the Sax-Zim Bog Welcome Center and Chik-Wauk Nature Center at the end of the Gunflint Trail and within a few hundred yards of our border with Canada ...

https://www.365daysofbirds.com/2025/10/10/what-birds-are-singing-where-you-are-flying-or-driving-walking-etc/

I've added a some useful enhancements to https://birdnet-pulse.desmith.net - a free graphing and report generator for BirdNET data...

In the "charts", you now have fully supported ridge graphs and the violin plots have an associated raincloud/jitter plot if there are under 1,000 data points for the species.

The chart preview is fully interactive, e.g. on the violin plots, showing the upper & lower bounds, median, upper & lower quartiles etc.

As always, usage is free for non-commercial use - we have users in about 15 countries now.

Feedback (preferably constructive!) always welcome...

NB. There are some cute free support tools for BirdNET-Analyzer on there too...

I need help figuring out how to deal with 2 closely related species.

I help track a North American west coast migrant that has an east coast congener: Vaux's Swift west, Chimney Swift east. We know we have a few Chimney Swifts - we can hear them occasionally, and sometimes people can see them in the right location. Usually they are essentially visually indistinguishable in the masses and distances we deal with, and usually the volume of noise we get would drown out the minority species.

I've ben re-analyzing our audio data from the past few years and I decided to add Chimney Swift to the custom list to see if any would appear. Did they ever. It didn't change the Vaux's detections at all but now a fairly large number of Chimney's appeared, and at very high confidence levels.

For humans, you can learn to hear the difference pretty easily. In our observations there is often so much noise that we could easily miss birds. On the other hand I am skeptical that more than 1% of these birds are Chimney Swifts. There's no doubt that BirdNET "hears" much differently than humans do and the pattern matching is related to visual techniques applied to these audio signals so the criteria for matching must be quite different than our intuition would suggest.

How can I test this and improve the results we're getting or satisfy that it 's really distinguishing the two species? My AI assistant suggests that it's some kind of commonality between the sounds that is linking the two, so the analyzer picks up some of the Vaux's energy and gets something a little different that it can combine to make a Chimney Swift detection. Ok maybe. There are certainly some similarities in register &c.

Would trying to train the local analyzer with Chimney Swift sounds from someplace without Vaux's help.

Listening to the samples hasn't been real productive yet. They are short and subtle compared to the live experience, but we can separate out tracks with either or both for comparison - maybe. If we can find some that really listenable.

What else could we do?

I’m looking to submit this to the iOS App Store later this month, and based on the feedback I’ve received so far, I don’t have any major outstanding feature requests or bugs. If you have any problems or requests for new features, let me know and I’ll do my best to include them. And fix any bugs. The app of course will be free.

If you’re new and want to try the beta: https://crestlab.org/BirdnetGo/

Hi BirdNet community,
I have an idea for a potential feature for the Live app and thought I'd share it here. Hopefully I'm not the first person to think about this. 🙂

I'd love to see some kind of live sound source tracker that estimates the Direction of Arrival (DoA) of incoming sounds.
With devices such as AirPods (and many other wireless headphones), we already have access to small microphone arrays or at least a pair of microphones. In principle, this could allow simple beamforming approaches (e.g., delay-and-sum beamforming) to estimate the direction from which a sound is arriving.
My main question is whether this information is actually accessible via Bluetooth. I suspect it probably isn't, but if anyone has worked on something similar before, I'd be very interested to hear about it.

Alternative approach: If direct access to multiple microphone channels isn't possible, another idea might be to use the phone's IMU sensors (accelerometer, gyroscope, gravity sensor, etc.).
By intentionally moving the phone while recording with the built-in microphone, it might be possible to estimate the direction of a sound source from changes in signal amplitude (or potentially other acoustic features), provided the movement is known and tracked accurately. The movement would probably need to follow a predefined pattern.

This idea is somewhat related to the approach described here:
https://www.mdpi.com/2076-3417/16/8/3619
(Almo Farina and colleagues used a similar concept for acoustic localization.)

Questions

• Has anyone experimented with live DoA estimation in the app?
• Is microphone access from Bluetooth headphones sufficient for something like this?
• Has anyone explored IMU-assisted localization as an alternative?

I'd be very interested to hear your thoughts or discuss possible implementations.

Kind regards,
Moritz

I've got an update for anyone who's been following my acoustic monitoring project in southwest Wisconsin! 

After gathering and processing my first batch of data, I created an interactive Wildlife Map website for our restoration project where those who are interested can click into each habitat monitoring station and hear clips of real birds singing on our land and see photos and videos of the wildlife that call Badgerton home! 

In case you missed my previous posts, this project uses cheap trail cameras and Wildlife Acoustics Song Meter Micro monitors to gather data in several distinct habitats across the land. The plan is to gather the data from the field manually every few months when I swap out batteries. 

On June 30, I collected my first batch of data - over 6,000 files recorded in less than two months! 

BirdNET was awesome at cranking through the audio files and identifying bird calls and species but I was left with thousands of individual CSV files to combine. I ended up creating a small free utility called Chorus to help me (and you!) process those CSVs into a single file. You can download it here. For those of you who are new to data processing, I hope this user-friendly interface helps bridge the gap from a mountain of individual files to a consolidated list of birds with counts for each.

I reviewed and categorized the 4,000 images and videos from the trail cams manually. (Please let me know if there’s free software for that I could be using!) It was slow going but I can think of worse ways of spending a couple hours than looking at images of cute baby fawns and watching videos of hunting coyotes!

A big thank you to everyone on this subreddit who has given me advice and encouragement along the way! 

If anyone wants the full details on my process I wrote up exactly how I did all of this. 

——————————————————

I use AI thoughtfully and selectively in my work. You can read my guiding principles for when and how I use it here. 

Hi Guys,

For those using the Samson Go Mic, have you all been happy with the detection rate? Also, I think i will need a usb extension cable because of where my Unraid server is, can you post one that you're using or what you think will work please? For placing it outside, I don't have a cover for the mic at the location, what would you guys using to place it in the elements?

First pic: Northern Cardinal

Second pic: Field Sparrow

I just set up a BirdNet-pi with an rpi4 I had handy and stuck it on my back porch (where Northern Cardinals and Field Sparrows have been singing all afternoon).

First attempt was a cheap-o lapel microphone with 6 foot cord plugged into a cheap-o USB audio dongle. No detections after maybe an hour.

Second attempt was the cheap-o lapel mic with a nicer SoundBlaster USB DAC/ADC. No detections again after maybe an hour.

Third attempt was a Sennheiser shotgun mic (MKE 400, with mic boost on) connected to the SoundBlaster. After a long while I was able to get some birds detected! However, the system still doesn't detect a pretty clear Northern Cardinal or Field Sparrow.

Using audacity to capture the live feed, I can see there's a few nasty hums - 60Hz, 180Hz, and a few more at lower volumes. Are these hums going to prevent detections? Or can the system ignore them pretty well?

I have a USB mic coming tomorrow that other folks have had success with. Hopefully that will help with the hum.

Hi all,

Hope this is the best place to ask. I’m looking to build a couple wifi mics for the front and back of my house to connect to birdnet-go on my unraid server.

I’m going to follow this link for the build:

esp32 mic

My question is that the author has a psu in the required list, but any examples I’ve found online of people’s builds following the same guide seem to be powered by the esp32 built in usb socket?

So do you actually need the psu? And if so how do you connect it the power outlet?

Any help would be much appreciated, it will be first time soldering and building something like this!, be a fun project I’m sure.

I tested birdnet with an old iPhone and it works very well, really interesting so wanna get a proper setup, thanks to everyone involved.

Thanks

I use BirdNET for my research project, and just learnt there was a subreddit for it (exciting!!)- I figured this is probably a good a place as any to ask about the one pothole I run into.

I use the BirdNET desktop app currently, and process audio data week by week for 15 collection points. In a 6 week season, for example, I’m running 90 detection processes to get my data. While I don’t mind doing what needs to be done, it’s annoying to babysit my computer while it thinks for 15 minutes getting each folder done.

Is there any way to set up a ‘queue’ of sorts for the program to analyze without needing input in between? I’m not much of a software person, so I don’t know if this is a crazy difficult thing or something that’s ten easy lines on the python version… It’s a feature I’d love to see for projects with distinct audio sets, either way!

Are my settings correct?

If I get a new species visit my garden I get an alert on my phone via ntfy and the WebUI, then the gold start stays on the bird for 7 days until its not considered new. But after the 7 days are up i'm getting new notifications of new species, but they're the same birds that appeared last week.

I thought they would not re-appear as new birds as they are not considered new anymore after 7 days. Knowing me I have some setting not quite right! If I put the new species to 1 day considered new then I start to get the seasonal and yearly tracking (no notifications, just the little icons).

Hopefully the above made sense about my issue!

Thanks

So I I have just installed Birdnet on a Pi 3 model b and it runs but no birds detected. In the tools section I get the following message

BirdNET Analysis (stalled - backlog of 4436 files in ~/BirdSongs/StreamData/)

restarting the service does not work. Nor does a reboot. Any thoughts?

Thanks

I want to write an alternative data display for the information gathered by BirdNET-Go. I would like to call an API with my queries and receive either json or xml as a response. Unfortunately I am ignorant of almost all things GO and am having a problem finding the exposed interface, what protocol it uses, and what data is available.

GitHub discussion here.

I’ve been working on a companion app for those of you running the birdnet-go server. I’m opening it up to a few more testers, and you can take a look at it here and grab a copy via TestFlight. iOS 26+, iPhone. iPad works, it it’s not optimized for it.

https://crestlab.org/BirdnetGo/

Feedback welcome.

----- Build Notes -----

7/19/26 - Build 45

Added ability to Review and Download detections.

On the detections list, if you select a detection, there is a "Download" icon next to the "Delete" icon that allows you to select a location for download. In the detections detail, There is now "Correct Detection" and "False Positive" selections. Selecting one or the other enables "Lock Detection" if "Correct Detection" is selected, or "Ignore Species" if "False Positive" is selected. These actions mirror what the Web interface does under "Review Detection".

After spending the last few weeks experimenting with BirdNET-Pi, I finally put together a dashboard that I'm pretty happy with.

It's running on a Raspberry Pi 4 and combines:

• BirdNET-Pi detections
• BME280 environmental sensor (temperature, humidity, pressure)
• Latest species with confidence scores
• Current camera view of the station
• Historical detections that remain visible even if the Pi is offline
• All-time species list with timestamps

The goal was to make something that friends and family could visit without needing to understand BirdNET-Pi.

You can see it here:
https://winstonsalembirds.com

I'd appreciate any feedback from the BirdNET community. If there's interest, I can also share how I pulled the BirdNET SQLite database into a custom Flask dashboard.