IBM and the World Wide Fund For Nature – Germany (WWF) have announced a partnership to develop a new AI conservation solution to support monitoring keystone species. This project will start with a focus on the critically endangered African forest elephant.
Indeed, habitat loss and poaching in the Congo Basin have resulted in an 80% decrease in their populations in recent years, it was shared.
The parties explained that the new solution will be designed to utilise AI-powered visual inspection to enhance elephant tracking, supporting the accurate identification of individual elephants from camera trap photos.
According to IBM and WWF-Germany, the goal is to support key conservation efforts of African forest elephants, which they said have been shown to increase carbon storage in their forest habitats.
IBM’s Maximo Visual Inspection (MVI) will be used in the collaboration. Its AI-powered visual inspection and modelling capabilities aim to analyse images from camera traps and film to identify individual African forest elephants with greater accuracy.
Currently, the use case focuses on head and tusk-related image recognition, similar to a fingerprint for humans.
Looking ahead, the parties said that the technology could also be used by organisations to “assess the financial value of nature’s contributions to people (NCP) provided by African forest elephants,” such as carbon sequestration ‘services.’
In addition, the two organisations shared that they aim to leverage IBM Environmental Intelligence to detect above-ground biomass and vegetation levels in specific areas where elephants are present.
This, they said, will enable more accurate predictions of the elephants’ future locations to better quantify the NCP services they provide and help quantify and tokenise the value of carbon services provided by the African forest elephant.
“Counting African forest elephants is both difficult and costly. The logistics are complex and the resulting population numbers are not precise,” said Dr. Thomas Breuer, WWF Germany – African Forest Elephant Coordinator. “Being able to identify individual elephants from camera trap images with the help of AI has the potential to be a game-changer. With AI, we will be able to monitor individual animals in space and time, giving us more robust and detailed population estimates and allowing for performance-based conservation payments, such as wildlife credits.”
“The spatial data will also show us where these elephants choose to move – thus enabling us to protect these wildlife corridors,” added Dr. Breuer.