DIY Bioacoustics
Summary
Non-invasive bioacoustic monitoring has become an increasingly effective way of monitoring ecosystem diversity and health.
Bioacoustics paired with machine learning has been cited as an effective way of automatically identifying animals such as frogs (Xie, 2017), birds (Zhao et al, 2017) and fish (Sattar et al, 2016) amongst other animals.
Bioacoustics is an area of scientific research which would benefit from (i) continued expansion of machine learning and automated identification of insect species (ii) creation of open source hardware for conducting research. Our aim is to contribute to (i) by applying bioacoustics and machine learning to insect recognition and to (ii) by creating an open source, diy and hackable acoustic sensor for identification of various insect species.
The Team
We are a group of designers adopting an transdisciplinary to the intersection between science, systems research, art, acoustics and design.
Davin Browner-Conaty, Service Design, Royal College of Art - Davin has an academic background in Philosophy graduating with a BA from Trinity College Dublin in 2016. He has done research both in bioacoustics and experimental audio research.
Minwoo Kim, Service Design, Royal College of Art - Minwoo has an academic background in Computer Science, Architecture and Media. He was a visiting lecturer and senior researcher at the University in the South Korea. Some of his previous research is based on biological phenomena such as emergence, complexity and self-organisation.
Alice Potts
Filippo Sanzeni, Service Design, Royal College of Art - Filippo has an academic background in Communication Design and is an active member of the DIY movement. He is currently working on various sound-systems, including a modular synthesizer.
Project Outcomes
Project Report
Project report and documentation on Github
Project Proposal
Original proposal and application
