Case Studies

Our global community of wildlife conservationists, scientists, tech innovators, and researchers have submitted case studies for the projects they are working on.

If you have any questions or have a case study of your own to submit, please get involved.

Using Machine Learning To Identify Birdsongs

New Zealand scientists are teaching AI to identify birdcalls, enabling them to discover the location and number of endemic birds and better understand and conserve threatened species.

Monitoring Seal Behavior & Population Stability With Accelerometers

The Marine Predator Research Group is working to conserve marine food webs, by monitoring behavioral changes in seals over time and identifying major drivers behind population changes. They are using machine learning to automatically detect seal behaviors from accelerometers.

Identifying Invasive Predators In New Zealand

The Cacophony Project is developing a set of technologies to identify and eliminate positively identified invasive predators in order to protect native New Zealand bird species. They are employing techniques to lure invasive predators with sound and light, observing them using thermal cameras, and using machine learning to automatically identify predators.

Using Drones & AI To Identify Poachers On The Ground

Africa’s losing its most at-risk species to poachers. At the current rate, elephants and rhinos will be extinct in the next 10 years. 400ft is using AI and drones to identify wildlife and poachers on the ground – allowing rangers to respond faster and stay safe while doing so.

Detecting plastic litter in natural environments

The Ocean Cleanup is using artificial intelligence algorithms to identify and remove plastics from natural environments before they harm wildlife.