Student uses AI to count hidden baby owls by their unique voices

Researchers have developed a way to count hidden baby barn owls from a distance by using AI and sound so they don’t have to disturb their nests.

Bournemouth University PhD student Kavisha Jayathunge is mapping the individual calls and using AI to distinguish between them to calculate how many owls are in the area.

He has successfully tested the technology and says it can be used to assess how hungry the owls are too.

“We’re using AI to count baby barn owls by sound instead of disturbing them in their nests with video cameras” Kavisha said.

“This helps reduce stress on the birds and could give us data from natural nest sites which are often inaccessible for monitoring not just the artificial nestboxes where most of the data we currently have comes from.”

The model developed by Kavisha can calculate the number of owls in the vicinity by being able to distinguish their individual calls.

The difference in sounds made by each baby owl would be indistinguishable to the human ear but the technology is able to pick out distinctions in frequency to map the number of birds as well as each individual bird’s identity.

Although it is still in the early stages of development testing has been successfully conducted in North Dorset.

“This basic data is important for monitoring breeding success of barn owls which can vary greatly between years and breeding sites” said Brian Cresswell a biologist turned electronics engineer who is working with Kavisha.

“The AI model is also a great research tool to study the behaviour of young owls and the purpose of their hissing which is believed to be a means to negotiate who will get fed at the next food delivery by their parents.

“There may also be potential for the hissing analyses to determine how hungry the owlets are which again is important data for monitoring breeding success.”

The longer term aim of the project is to develop the technology so volunteers and conservationists can take audio recorders out into nature to capture the sounds of hissing owlets at their nests.

Barn owl hissing is loud so recorders can be placed away from nests to avoid disturbance.

“It has great potential for citizen science as it doesn’t require expensive and specialist equipment – anyone could gather recordings and send them for analysis” Kavisha said.

“By making barn owl nest monitoring more scalable and less invasive we hope this project can contribute to better long term outcomes for the species.”