AI for Wildlife Conservation
Discover how AI applications help combat wildlife poaching through predictive modeling and drone surveillance. This lesson covers real case studies of AI tools like PAWS, which uses machine learning and game theory to design patrol routes, and Air Shepherd, which employs drones and deep learning for night-time poacher detection. Understand the challenges and innovative AI strategies protecting endangered species.
We'll cover the following...
Background
“We use data to not only make better decisions about what kind of movie we want to see but also what kind of world we want to see.”
As the human population keeps booming, our actions are pushing life on our shared planet towards mass extinction. Human activity is causing extinctions at the rate of centuries versus the millions of years that it takes for natural extinctions. Poaching is playing a huge role in this human lead devastation, and the numbers for some species are plummeting to critical/unsustainable levels. According to the Lindbergh Foundation:
To combat poaching and to rebuild the populations of the endangered species, some countries have set up protected wildlife reserves and conservation agencies, tasked with defending these large reserves. However, these efforts have not been good enough to counter poaching. Poachers have gone high-tech, using night-vision goggles and GPS to kill elephants and rhinos for their tusks and horns. Therefore, because patrolling is used as the primary method for securing large reserves, it is necessary to create Smart ...