Bird@Edge Mic is an audio streaming appliance based on an ESP32 and an I2S microphone intended for soundscape recordings of birds.

Bird@Edge is an Edge AI system for recognizing bird species in audio recordings to support real-time biodiversity monitoring. Bird@Edge is based on embedded edge devices operating in a distributed system to enable efficient, continuous evaluation of soundscapes recorded in forests. If you are interested in our research, read our paper or watch the talk recorded for Springer NETYS 2022 conference.

Separate repositories exist for the machine learning approach and for the operating system image Bird@Edge OS created for running on the Bird@Edge Stations.

An integrated web-server offers a (single) WAV-stream consisting of the data comming directly read from the microphone. The WAV header is constructed according to the configuration used for i2s.

Note: The stream can only be accessed by a single HTTP client, as there is no buffering, etc. involved.

First, the i2s microphone needs to be connected according to the pinout definition in the code:

const i2s_pin_config_t pin_config = {
    .bck_io_num = 14,   // BCKL
    .ws_io_num = 15,    // LRCL
    .data_out_num = -1, // not used (only for speakers)
    .data_in_num = 32   // DOUT
};

An examplary board which can be used in the project is the Adafruit HUZZAH32 Feather, its pinout is presented here:

The project can be built and flashed using the PlatformIO toolchain.

$ pio run -t upload      
Processing esp32dev (platform: espressif32; board: esp32dev; framework: arduino)
-----------------------------------------------------------------------------------------------------------------------------------------------
Verbose mode can be enabled via `-v, --verbose` option
CONFIGURATION: https://docs.platformio.org/page/boards/espressif32/esp32dev.html
PLATFORM: Espressif 32 (3.5.0) > Espressif ESP32 Dev Module
HARDWARE: ESP32 240MHz, 320KB RAM, 4MB Flash
DEBUG: Current (esp-prog) External (esp-prog, iot-bus-jtag, jlink, minimodule, olimex-arm-usb-ocd, olimex-arm-usb-ocd-h, olimex-arm-usb-tiny-h, olimex-jtag-tiny, tumpa)
PACKAGES: 
 - framework-arduinoespressif32 3.10006.210326 (1.0.6) 
 - tool-esptoolpy 1.30100.210531 (3.1.0) 
 - tool-mkspiffs 2.230.0 (2.30) 
 - toolchain-xtensa32 2.50200.97 (5.2.0)
LDF: Library Dependency Finder -> https://bit.ly/configure-pio-ldf
LDF Modes: Finder ~ chain, Compatibility ~ soft
Found 28 compatible libraries
Scanning dependencies...
Dependency Graph
|-- <WiFi> 1.0
Building in release mode
Compiling .pio/build/esp32dev/src/main.cpp.o
Generating partitions .pio/build/esp32dev/partitions.bin

If you are using Bird@Edge in academia, we'd appreciate if you cited our scientific research paper. Please cite as "Höchst & Bellafkir et al."

J. Höchst, H. Bellafkir, P. Lampe, M. Vogelbacher, M. Mühling, D. Schneider, K. Lindner, S. Rösner, D. G. Schabo, N. Farwig, and B. Freisleben, "Bird@Edge: Bird Species Recognition at the Edge," in International Conference on Networked Systems (NETYS), 2022. DOI: 10.1007/978-3-031-17436-0_6

@inproceedings{hoechst2022birdedge,
  title = {{Bird@Edge: Bird Species Recognition at the Edge}},
  author = {H{\"o}chst, Jonas and Bellafkir, Hicham and Lampe, Patrick and Vogelbacher, Markus and M{\"u}hling, Markus and Schneider, Daniel and Lindner, Kim and R{\"o}sner, Sascha and Schabo, Dana G. and Farwig, Nina and Freisleben, Bernd},
  booktitle = {International Conference on Networked Systems (NETYS)},
  year = {2022},
  month = may,
  organization = {Springer},
  keywords = {Bird Species Recognition, Edge Computing, Passive Acoustic Monitoring, Biodiversity},
  doi = {10.1007/978-3-031-17436-0_6},
}