Let’s Create a BirdNET-Pi!
Welcome to our BirdNET-Pi workshop. In this workshop, we will guide you step by step through the process of setting up your own BirdNET-Pi.
This is a fun and educational project that allows you to automatically monitor and identify birds singing in your backyard, garden, or balcony.
By the end of the workshop, you will have a fully working system that can record bird sounds, analyze them locally, and display detected species through a web interface.
What is BirdNET-Pi?
Section titled “What is BirdNET-Pi?”BirdNET-Pi is a lightweight, open-source system that brings AI-based bird sound recognition to small, affordable hardware such as a Raspberry Pi.
It enables continuous acoustic monitoring by automatically detecting and identifying bird species from audio recordings.
At its core, BirdNET-Pi runs a machine learning model locally on the device, meaning all audio processing and species classification happen directly on the Raspberry Pi.
A key advantage of BirdNET-Pi is that no internet connection is required. The system works fully offline.
Although BirdNET-Pi continuously analyzes audio, it is not strictly real-time.
Audio is processed in segments (e.g., 6–60 seconds) and analyzed sequentially, which introduces a short delay between recording and detection.
This behavior is configurable, allowing users to adjust recording length and processing intervals to balance speed and performance.
All results and system information are available through a web-based interface, where users can:
- View detected species and timestamps
- Access spectrograms and audio snippets
- Monitor system status
- Adjust settings and parameters
BirdNET-Pi is a community-driven, open-source project available on GitHub, enabling researchers, educators, and developers to use, modify, and extend the system. Are you interrested in the project? Check out the GitHub repository.
To address privacy concerns, BirdNET-Pi includes human detection, which helps filter recordings containing human voices.