AI techniques in wildlife conservation

AI techniques in wildlife conservation

It is expected that 38% of the species as we know of will be extinct by 2100. In fact, just a few days ago, the first animal extinction of the new calendar year was confirmed: the Chinese paddle fish. This threat applies to Africa too, as Panthera leo has lost over 40% of their natural terrain over the last 20 years. The loss of land has forced animals to roam more extensively across a very fragmented landscape, which difficult's the tracking efforts.

Several AI applications for wildlife conservation include computer vision solutions as their primary thrust. In particular, image recognition and classification processes have had significant positive animal preservation results. The approach was along the same lines.

Historically conservationists identify lions by manually analyzing precise whisker patterns in each animal. Facial whiskers do not change frequently throughout an animal’s life, and this makes it possible to recognize each individual animal over time, by observing their whisker patterns alone. This thorough examination was performed by conservationists, who had to compare whisker photographs with a predefined grid and isolate the unique design that matched the specific animal being analyzed from a database of over 400 lions.

The tool chains consist of computer vision and pattern recognition algorithms that can automatically perform the different methods for lion identification: face and whisker id. This reduces time spent and the number of human resources required allowing conservationists to viably use large data sets in their work.