Radio Brisvaani
Bravus Mining and Resources has partnered with Queensland scientists to use cutting-edge artificial
intelligence technology to improve remote monitoring of the Black-throated Finch at the Carmichael mine
near Clermont in central Queensland.
Researchers from E2M created an automated recogniser to capture the birds’ calls, which will support best
practice monitoring of the species and open the door for better surveillance of other rare birds.
In a new scientific article published in the international journal Ecological Informatics, the researchers
detailed the use of machine learning to make major advances in the technology used to analyse
bioacoustics data.
Bravus Mining and Resources Chief Operating Officer Mick Crowe said this latest research and innovation
built on the company’s comprehensive work to protect the local finch population.
“We developed a targeted Management Plan to protect local Black-throated Finches and their habitat as
part of the strict environment conditions our Carmichael mine operates under,’’ Mr Crowe said.
“Research undertaken over many years now shows those plans are working and the finches are thriving.
“However, our work is also contributing a new understanding of the species and this exciting development
to unlock new monitoring technologies will help to improve the management of finch populations more
broadly in Queensland.
“Innovations like this help ensure our Management Plan remains world’s best practice and that we
continue to mine in a way that is responsible and creates jobs and business opportunities for regional
Queenslanders for generations to come.”
E2M Senior ecologist John van Osta said the research was developed in consultation with the Queensland
Department of Environment and Science and would support the development of automated recognisers
for other rare and difficult-to-survey bird species.
“The publication of this work in a respected scientific journal shows our commitment to scientific rigour
and supports research and management of Black-throated Finch throughout their range,’’ he said.
“This research will support best practice monitoring for the species and will provide valuable insights for
others working to study and protect this species around Queensland.”
Machine learning is a type of artificial intelligence and computer science where computers use data and
algorithms to improve the accuracy of their performance, imitating human learning.
Contact: media@bravus.com.au
+61 438031780
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The innovation comes only months after world-first research into the Black-throated Finch found
populations of the bird are thriving at Bravus Mining and Resources’ Carmichael mine.
To support the management of the finch population, Bravus uses bioacoustics recordings to help track bird
movements and to identify individual bird’s home ranges, providing insights into their day-to-day
behaviour.
While bird calls can be recorded and later manually analysed, automated recognisers can instantly detect
the target bird call and are a more accurate way to detect bird species than even visual surveys.
However, they typically require many examples of bird vocalisations to accurately train.
To produce a more accurate automated recogniser for the Black-throated Finch, researchers used more
than 9000 hours of audio recordings of the species in the Carmichael mine conservation area.
Using machine learning methods more common in medical imaging analysis and natural language
processing, the program was taught how to target data to improve the finch model and manage ambiguous
bird calls.
The result was an automated recogniser with a library of more than 1000 Black-throated Finch calls and a
model that can successfully identify the birds as well as human experts in the field.
