Animal and environmental conservation and research work is critical to maintaining our planet and the diverse species that inhabit it. Prior to the technological advances of the past few decades, researchers and experts have had to dedicate hours and days of their time to observing habitats, the majority of that time being spent waiting between sightings of the animal in question.

Camera traps have significantly aided experts and researchers. But now the task is in the sifting through of the camera trap image captures to identify the animals, differentiate between animals triggering the image capture versus the wind or other non-animal triggers. Currently, too many hours are spent in identifying and sifting through camera trap images. Efficiencies are needed in this area, and there is immense promise in applying artificial intelligence and computer vision to intensive video processing work and freeing up more time for humans to focus on interpreting the content and using the results.

There is immense promise in applying artificial intelligence and computer vision to intensive video processing work of camera traps for animal conservation. This could free up experts to dedicate their skills and time to interpreting the content and using the results to make meaningful impact on animals, ecosystems, and the planet.

1. Driven Data: Project Zamba -https://zamba.drivendata.org/

2. National Geographic - https://www.nationalgeographic.com/animals/2018/11/artificial-intelligence-counts-wild-animals/

Giving Tech Labs Team - giving.tech