![IBM's AI-Powered Visual Inspection Tech to Track Endangered African Forest Elephant IBM's AI-Powered Visual Inspection Tech to Track Endangered African Forest Elephant](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh0d6stwamyH8cwr5YcaToqMQ4YadwYJ1G59KT-6zvKoStv3-khLBwcMkpSTUaOIcs7Ifj2BT2gytL0Ts4Jzrm92fl3SVj9kEz-eIygmqJa8B6rrwU6cwDTix9CdV7P0zn1KJolqeI0BPBcK3j3AoBaPAsM8fDVtBx0PT11UssMJrnpjd_uXP1geoCrBQU/s16000-rw/20240814_125756_0000.png)
IBM and WWF-Germany to Build New AI Solution to Support Conservation of Keystone Species
IBM and WWF-Germany have announced a collaboration to develop a new AI solution aimed at supporting the conservation of keystone species, starting with the critically endangered African forest elephant.
The African forest elephant has experienced an over 80% decrease in their populations in recent years due to habitat loss and poaching in the Congo Basin. As businesses work to address climate change, supporting nature restoration can play a critical role in reducing carbon emissions in the atmosphere.
This initiative will leverage IBM's AI-powered visual inspection technology to enhance elephant tracking and identification from camera trap photos. The goal is to improve the accuracy of identifying individual elephants, which is crucial for effective conservation efforts.
By harnessing the power of technology to track and value natural capital, organizations can unlock new opportunities to support climate change mitigation efforts, while also identifying new sustainable finance investments.
This technology not only aids in wildlife conservation but also helps in assessing the financial value of nature's contributions, such as carbon sequestration services provided by these elephants. This collaboration marks a significant step towards integrating technology with conservation to create a more sustainable future.
As part of this collaboration, IBM Consulting worked with WWF to explore opportunities for innovation, aligning WWF's conservation initiatives with IBM's sustainability and technology expertise. IBM's own software, IBM Maximo Visual Inspection (MVI), will be used in this collaboration. Leveraging MVI's AI-powered visual inspection and modeling capabilities, the solution aims to analyze 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.
The goal of this solution is to help support key conservation efforts of African forest elephants, which have been shown to increase carbon storage in their forest habitats .
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