The UK uses AI technology to track 30 species of wild birds through sound recognition

In order to solve the growing biodiversity problem in the UK, the Zoological Society of London (ZSL) has partnered with Network Rail to develop a new wildlife monitoring method using artificial intelligence technology

After testing at three locations, the technology successfully captured the sounds and images of various animals, which were analyzed and positioned by computers. It is able to discern dozens of different bird species from their calls, while also accurately identifying animals such as foxes, deer, hedgehogs and bats without the involvement of a human observer

"We Tens of thousands of data files and thousands of hours of audio were collected, and a variety of animals were discovered within them, thanks to artificial intelligence at a scale we wouldn't be able to achieve with only human observers."

In this project, we chose three test sites located next to the railway. They are Barnes, Twickenham and Lewisham. These areas are owned by Network Rail. British Rail plays an important role in the project, covering more than 52,000 hectares of land, many of which play an important role in protecting the country's biodiversity. The areas are fenced to prevent people from straying onto the tracks, and maintenance crews rarely enter.

ZSL and British Rail plan to expand the use of AI monitors to other areas, including Chobham and New Zealand Forest and other surrey areas. Dancer said: "In the sites we have tested, we have found evidence of more than 30 species of birds and six species of bats, as well as animals such as foxes and hedgehogs, which has made us pleasantly surprised by the relatively healthy wildlife numbers in the London area. However, , the main aim of our project is not just to spot these animals, but to show how AI-led technology, combined with acoustic and camera traps, can effectively survey wildlife on UK railway land and can be carried out in other UK areas. This will Help us understand how species respond to climate change and guide our management of vegetation next to railways, on road edges and elsewhere." Machine learning and artificial intelligence are critical to protecting biodiversity, Dancer noted

machine Learning technologies will play a key role in protecting biodiversity, providing more precise data support by analyzing tens of thousands of hours of recordings and hundreds of thousands of images

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