AI reduces wildlife monitoring workload in Australia
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In northern Australia, Aboriginal rangers saw an 81.4 percent reduction in photo processing tasks when using artificial intelligence to monitor wildlife.
Researchers from Charles Darwin University studied a wildlife monitoring program in the Warddeken Aboriginal Protected Area in Western Arnhem, Australia. The program uses camera traps to observe animals important for cultural and conservation reasons, and ensures involvement from traditional landowners and rangers in land management.
Researchers from Warddeken Land Management, Charles Darwin University, and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) applied an AI-based wildlife identification system called ‘MegaDetector’ to 1,572 hours of data rangers collected. The technology reduced the number of images needing detailed analysis from 925,880 to 172,290. This decrease also cut the time spent processing photos from six months to two months, allowing rangers to spend more time on land management, identifying species, and documenting local languages and creating educational materials.
The study suggests AI can improve wildlife monitoring and support the preservation of Aboriginal cultural knowledge.
