AI BriefingHow the Open-Source AI Model SpeciesNet Helps Protect Wildlife
Key point
The open-source AI model SpeciesNet automatically analyzes vast amounts of camera trap data, supporting wildlife conservation efforts.
Details
Analyzing the vast number of wildlife photos collected through motion-detection cameras is an extremely time-consuming task. The open-source AI model SpeciesNet is revolutionizing this process by automatically identifying approximately 2,500 species of mammals, birds, and reptiles.
SpeciesNet has been used through Wildlife Insights since 2019, and since being released as free and open-source a year ago, it has dramatically accelerated data analysis for research groups around the world.
Key use cases include the following:
- Snapshot Serengeti (Africa): Analyzed 11 million photos from Serengeti National Park in Tanzania in just a few days, capturing animal behavior and population changes.
- Humboldt Institute (Colombia): Uses the Red Otus network to analyze bird migration timing and changes in wildlife activity patterns. The analysis revealed that some mammals are becoming more nocturnal to avoid threats.
- Idaho Department of Fish and Game (USA): Significantly reduced expert review time by pre-sorting millions of images collected each year by species.
- Wildlife Observatory of Australia (Australia): Further trains the model to identify local species.
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