Open jcmolloy opened 7 years ago
Some more information about the project:
Insects are vectors of diseases while also pollinating a large proportion of the world’s food production. Further to this, they also constitute a growing food market which is expected to be worth 55 billion dollars by 2023. Our aim is to apply bioacoustics and machine learning to insect recognition.
The Team Davin Browner-Conaty - has an academic background in Philosophy, currently is studying Service Design at Royal College of Art. He has done research both in bioacoustics and experimental audio research.
Minwoo Kim - has an academic background in Computer Science, Architecture and Media, currently is studying Service Design at Royal College of Art. He was a visiting lecturer and senior researcher at the University in the South Korea.
Filippo Sanzeni - has an academic background in Communication Design, currently is studying Service Design at Royal College of Art. He is currently working on various sound systems, including a modular synthesiser.
Our interdisciplinary background matched with our current learning environment at the RCA will contribute to a project which is both innovative and grounded in a fruitful intersection of art, design, science and audio research.
We are looking for field biologists, entomologists, and anybody who has previously worked with audio and optical sensors.
Contact: filippo.sanzeni@network.rca.ac.uk
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.
Looking for: biologists
Contact: Filippo Sanzeni