{"id":28120887,"url":"https://github.com/audevuilli/shazam4bb","last_synced_at":"2025-09-05T03:40:30.878Z","repository":{"id":49408843,"uuid":"476293809","full_name":"audevuilli/Shazam4BB","owner":"audevuilli","description":"Shazam for Bats \u0026 Birds - A realtime acoustic birds and bats classification systems built on the TFLite version of BirdNet. 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This project facilitates the adoption of technology to monitor the calls of birds and bats and learn about the different species populated a local area. It provides easy-to-follow documentation to build and install the device as well as to visualise in real-time bats and birds calls. This project hopes to gain better understanding of how birds and bats species are distributed and adapted to various environment.\n\n### Minimal Viable Project\nShazam4BB is a DIY birds and bats species audio classification device, which consists of both hardware (microphone, single-board computer) and software (classification algorithm and web server). To make it viable, a bats or birds species algorithm has to be implemented, an internet connection has to exist, and results have to be saved into a database. \n\n1. Process: Audio recording. Microphone. Single-board computer with Audio Input.\n2. Analysis: Audio analysis. Deep-Learning Algorithm to identify species in spectrogram.\n3. Visualisation: Audio results. Save result in database. \n4. Components: Microphone, Computer Processing Unit (CPU, GPU), Power module, Communication (Wifi, LoRa) Module\n\nShazam4BB is a on-going project. It has started with the help of the [**Open Hardware Makers (OHM)**](https://curriculum.openhardware.space/) and [**GOSH's 2022 Collaborative Development**](https://forum.openhardware.science/t/apply-here-for-gosh-s-2022-collaborative-development-program-round-1/3380)  programmes. The aim of this project is to improve the technical capability of the 4 years old [\"Shazam for Bats\"](https://connected-environments.org/portfolio/shazamforbats/) project by migrating from an Intel Edison board to a Raspberry Pi board.  \n\n#### Team\nThe team behind this project is composed of PhD Students, Professors, and Practitioners in the field of ecology and engineering based at the [Connected Environments Lab](https://connected-environments.org/) at The Bartlett CASA, at the [People and Nature Lab](https://www.ucl.ac.uk/biosciences/gee/people-and-nature-lab/) at the Centre for Biodvierstiy and Environment Research CBER at UCL. \n\n#### Specific Goals\nThere are similar open-hardware projects outhere that monitor and classify birds or bats in real-time. The project is specific for the following reasons:\n- Classify bats in real-time on a Raspberry Pi. \n- Document the device enclosure. \n- Optimise for long-range transmission and low-power consumption. \n- Allow classification of Birds and Bats on the same device. \n\n### Similar Projects\n- [BirdNet-Pi](https://github.com/mcguirepr89/BirdNET-Pi) by Patrick McGuire [@mcguirepr89](https://github.com/mcguirepr89) under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 Internation Public License.\n- [RPi-Eco-Monitoring](https://github.com/sarabsethi/rpi-eco-monitoring) by Sarab Sethi [@sarabsethi](https://github.com/sarabsethi) under a GNU General v3.0 Public License. \n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faudevuilli%2Fshazam4bb","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faudevuilli%2Fshazam4bb","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faudevuilli%2Fshazam4bb/lists"}