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Low Cost Audio Recorders for the Forests

posted Aug 24, 2020, 9:44 PM by MUHAMMAD MUN`IM AHMAD ZABIDI   [ updated Sep 11, 2020, 6:10 AM ]

Custom board with the Gecko processor from Silicon Labs. The Gecko contains the ARM Cortex-M4. The whole board is powered by 3 x AA batteries, uses an analog MEMS microphone and records up 384kHz. Open source. Created by 2 PhD students at the University of Southampton, Andrew Hill and Peter Prince together with Rogers, a professor at Oxford. Audiomoth can be ordered from Labmaker. Publications:
  • Andrew P. Hill, Peter Prince, Jake L. Snaddon, C. Patrick Doncaster, Alex Rogers. AudioMoth: A low-cost acoustic device for monitoring biodiversity and the environment. HardwareX.
  • Hill AP, Prince P, Piña Covarrubias E, Doncaster CP, Snaddon JL, and Rogers A (2017). AudioMoth: Evaluation of a smart open acoustic device for monitoring biodiversity and the environment. Methods in Ecology and Evolution.
  • Prince P, Hill A, Piña Covarrubias E, Doncaster P, Snaddon JL, Rogers A. Deploying acoustic detection algorithms on low-cost, open-source acoustic sensors for environmental monitoring. Sensors. 2019 Jan;19(3):553.

Uses Raspberry Pi A+ or B. The web page recommends Rode SmartLav+ microphone. From a PhD project by Sethi et al (2018) at Imperial College. Data is transmitted via GSM. Publications:
  • Sarab S. Sethi,  Robert M. Ewers,  Nick S. Jones,  Christopher David L. Orme  and Lorenzo Picinali (2018), Robust, real‐time and autonomous monitoring of ecosystems with an open, low‐cost, networked device. Methods in Ecology and Evolution.
  • Sethi, S. S., Ewers, R. M., Jones, N. S., Signorelli, A., Picinali, L., & Orme, C. D. L. (2020). SAFE Acoustics: an open-source, real-time eco-acoustic monitoring network in the tropical rainforests of Borneo. Methods in Ecology and Evolution.
Press:

The Bela Mini is a device running Cortex and CMSIS-NN. It is created at Queen Mary University of London. It implements the 'bulbul' CNN model proposed by Grill and Schlüter, winner of the 2016 Bird Audio Detection Challenge. Publications:
  • Solomes, Alexandru-Marius and Stowell, Dan (2020), Efficient Bird Sound Detection on the Bela Embedded System, ICASSP 2020.
  • T. Grill and J. Schlüter, Two convolutional neural networks for bird detection in audio signals, 2017 25th European Signal Processing Conference (EUSIPCO), pp. 1764-1768, Aug 2017.

PANDI


Developed in collaboration with the Royal Society for the Protection of Birds (RSPB) and the British Trust for Ornithology (BTO). Customizable, its core has two parts. One, the PANDI control node (PCN) uses the ESP32 microcontroller. Two, the PANDI acoustic sampling node (PASN) uses the Raspberry Pi Zero. The system detects two hard to sample species: the Eurasian Bittern (Botaurus stellaris) and the Corn Crake (Crex crex). Data is transmitted using LoRa. Publications:

Solo


Raspberry Pi based. Designed at the University of Stirling. Paired with the Cirrus Logic audio card. Combined with Peersonic RPA2 bat recorder, it became the AURITA. Publications:
  • Whytock, R. C., & Christie, J. (2017). Solo: an open source, customizable and inexpensive audio recorder for bioacoustic research. Methods in Ecology and Evolution, 8(3), 308-312.
  • Beason, R. D., Riesch, R., & Koricheva, J. (2019). AURITA: an affordable, autonomous recording device for acoustic monitoring of audible and ultrasonic frequencies. Bioacoustics, 28(4), 381-396.


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