Haikubox offers an AI-powered device that identifies bird songs in real-time, providing users with alerts and sound recordings. The device also delivers insights into bird behavior and migration patterns, enabling bird enthusiasts and researchers to monitor avian activity.
Funding
Funding not disclosed
Founders
Product
Problem
Identifying bird songs and calls in real-time typically requires specialized knowledge and constant attention, making it difficult for casual bird enthusiasts and researchers to monitor avian activity effectively. Existing methods often lack the ability to automatically record and analyze bird vocalizations for comprehensive insights.
Solution
Haikubox is an AI-powered device that automatically identifies bird species by their songs and calls, providing real-time alerts and recordings directly to a user's smartphone app and online account. The device uses a proprietary neural network trained on a vast dataset of bird sounds to accurately recognize individual species. By continuously listening and recording three-second sound samples, Haikubox enables users to track bird activity, learn about migration patterns, and contribute to community science initiatives. Users can customize alerts for new or favorite birds, access vivid images and spectrograms of identified species, and download their data for further analysis.
Target Audience
The primary audience includes bird enthusiasts, nature lovers, educators, and researchers interested in monitoring and studying bird populations and behavior in their backyards or local environments.
Features
- Real-time bird species identification using a proprietary neural network (BirdNet for Haikubox)
- 24/7 monitoring and recording of bird songs and calls
- Automatic sound recording and data sharing to the Haikubox app (iOS and Android) and website
- Customizable alerts for new or favorite bird species
- Access to images, sound recordings, and spectrograms of identified birds
- Data download in CSV format for analysis
- Adjustable privacy settings to control data sharing and location visibility
- Ability to label correct and incorrect identifications to improve the neural network's accuracy
- Integration with community science initiatives through collaboration with the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology