The idea is that Artificial Intelligence could replace invasive collars and tags.
Tracking specific animals usually involves conservationists attaching some form of device on the animals' bodies. So, when some software developers noticed the rapid growth of AI for human facial recognition, they wondered whether this could be used for conservation efforts too.
Their idea, combined with inspiration from an Alaskan webcam broadcasting brown bears from Canada's Katmai National Park, resulted in the development of BearID, a system that uses AI facial recognition to track specific bears and monitor population health. The software developers worked with biologists to match their tech knowledge with biological research and develop the programme.
Combining their skill sets, they all volunteered spare time over several years for this passion project that would eventually bear fruit, reporting the results of their experiment last week in the journal Ecology and Evolution. The project could help conservationists monitor the health of bear populations in various parts of the world, and perhaps aid work with other animals, too.
Using AI to differentiate bears is not an easy task. Unlike giraffes or zebras, they have no unique individual markings, so the researchers focused on eye, nose, and ear positioning to train an AI system to recognize individual bears. After training the system with 3,740 photographed bear faces, the system learned to recognize them on its own.
Now that BearID is up and running, the researchers are tracking specific grizzly bears in Knight Inlet, Canada with 84 percent accuracy. This use of AI for conservation offers a more accurate and comprehensive, as well as less invasive, method for monitoring bear populations and their behaviors. As the team continues to perfect BearID, no doubt their solution will be a viable option in other regions and for other animals, to the great on-going benefit of biologists and conservationists.