BirdNET is used in a biodiversity monitoring device to support real-time bird sound recognition in natural surroundings. The device listens to sounds from the environment and records them when something is heard. Once a sound is captured, BirdNET processes the audio to identify which bird species it belongs to. This setup allows us to keep track of local bird life automatically. It gives useful information about which birds are around and when they are active, helping us better understand changes in the area’s wildlife over time.
BirdNET is built on open-source principles, combining artificial intelligence with public accessibility. It uses a convolutional neural network (CNN) trained to recognize bird species based on their vocalizations. As free software, BirdNET’s models and code are openly available,allowing anyone to study, use, or improve them. This openness supports community-driven biodiversity research, especially in areas with limited resources. Combined with open hardware, BirdNET shows how free technologies can democratize environmental monitoring and promote scientific transparency worldwide.
