HERE’S HOW AI is helping tackle rhino
poaching in South Africa South Africa’s Department of Environment, Forestry and Fisheries in February announced that rhino poaching has continued its decline in the country. by Daniel Mpala
1ST QUARTER 2020
THE DEPARTMENT said 594 rhino were poached in 2019 compared to 769 in 2018. It attributed the decline, among other things, to improved capabilities to react to poaching incidents linked to better situational awareness and deployment of technology. Although an arsenal of technologies have been used in the fight against rhino poaching in South Africa, it’s worth noting the role artificial intelligence (AI) is playing. Among those at the forefront of the fight against rhino poaching has been trans-frontier conservation non-profit Peace Parks Foundation. About two years ago Peace Parks, in collaboration with Ezemvelo KZN Wildlife and working closely with Microsoft installed an AI-powered system comprised of 150 cameras in a number of rhino reserves managed by Emzemvelo in the KwaZulu-Natal province. When triggered, the camera traps send an email of the captured image to Peace Parks’ proprietary AI solution – SnapCatch – which then makes use of Microsoft Azure functions to identify any people or vehicles in the photo. In instances where people or vehicles are detected – positive detections – the SnapCatch app sends the photo to rangers as an alert with a GPS location, as well as information
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on the target’s direction of travel. Doug Gillings, who heads up the Peace Parks’ Combatting Wildlife Crime department, said in February that the solution is “very simple and straightforward” to operate from a field or game reserve perspective. “You create an account on the SnapCatch app, configure the alert process and then add the email address that it generates to the legacy camera trap,” explained Gillings. The system is not without its difficulties. He pointed out that due to the remoteness and harshness of the environment in which the solutions are deployed in, maintaining the hardware’s batteries, data management and protecting from damage by wildlife are big challenges. “Keeping the complexities and customisations server side, has simplified things significantly as the solution is hardware agnostic and very cheap to replace,” said Gillings The need for AI The more than 150 cameras that make up the system generate more than 28 000 images a month. Gillings pointed out that sifting through all this data to find poachers, as well as reserving staff time to find valid information from among the false positive detections –
