AI catching wildlife poachers

2 poachers captured in 1st week


Doubled the detection rate

human error


Wildlife Conservation


AI Technique

Computer vision trained on images sources from WPS field cameras

Motion detection cameras transmit images to the Wildlife Protection Solutions head office in real time where they are assessed by a team member for evidence of people, vehicles or poaching. This is a slow and labour intensive activity, prompting WPS to look for a solution to streamline the process. 

Silverpond used its tool HighLighter to train a deep learning model to recognise suspected poachers quickly by analysing video streams. 

-Doubled detection rate (40% to 80%).
-Seamless integration into existing system.
-Two poachers captured and detained within first week of deployment.
-Over 1 million inferences in the first year alone.

A CUSTOM AI MODEL WAS developed to account for the types of images captured by WPS’ cameras in the field
The AI model can identify objects of interest without being distracted by other components of the image
The AI model also detects various animals such as Elephants, giraffes and lions

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