Researchers at the University of Southern California have developed Protection Assistant for Wildlife Security (PAWS), an artificial intelligence program that uses machine learning algorithms to analyze data from past animal patrols to predict where poaching is likely to occur.
Meanwhile, a game theory model helps generate randomized, unpredictable patrol routes.
PAWS has produced good results during field tests in Uganda and Malaysia, and in the coming year its use will expand to China and Cambodia.
The PAWS system also could be integrated into an existing tracking tool called SMART, which wildlife conservation agencies have deployed at most sites around the world to collect and manage patrol data.
The researchers say the next step for PAWS is to make it available to other non-governmental organizations by integrating the algorithm into existing tools.
They also are working with a wildlife conservation service that uses drones equipped with infrared cameras to search for poachers at night.
From IEEE Spectrum
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