If wildlife conservation interests you, keep reading
What's the story
Artificial intelligence is revolutionizing wildlife conservation by processing vast amounts of data from cameras, drones, and sensors to safeguard endangered species and habitats in real time. From anti-poaching efforts to population monitoring, certain AI tools are offering actionable insights through global case studies. These tools are enabling conservationists to make informed decisions to protect biodiversity against challenges like poaching, habitat loss, and other threats.
#1
EarthRanger's real-time monitoring
EarthRanger, a brainchild of AI2 and Vulcan Inc., combines GPS collars, camera traps, and ranger reports into a dashboard for real-time monitoring. It predicts poaching activities in South Africa, Southeast Asia, and other regions. Using NVIDIA-accelerated machine learning, it also tracks rhinos and predicts elephant movements near human boundaries. This prevents crop raids and retaliation, while assisting patrol planning in big parks like Serengeti.
#2
TrailGuard AI cameras for anti-poaching
TrailGuard AI cameras are a breakthrough in anti-poaching. They instantly identify species, humans, or vehicles, and alert rangers via satellite. Deployed in Yellowstone and African reserves, these hidden systems detect tigers to warn livestock owners or flag gunshots and wolf behaviors for quick responses. In one case, it spotted a limping panther, enabling quick intervention.
#3
Wildtrack AI's accurate analysis
WildTrack AI provides incredible footprint analysis with more than 95% accuracy, even in low-light conditions. It also supports ranger apps for endangered species databases by analyzing camera trap data easily. This way, the tool helps conservationists by giving them accurate information about animal movements, something that is critical for protecting endangered species.
#4
Wildbook's global impact on species classification
Wild Me's Wildbook employs computer vision on 14 million crowdsourced photos to classify whale sharks and other species, helping 2,000 researchers around the world. Zooniverse Wildlife AI takes this a step further with citizen science, gamifying image classification across more than 50 projects worldwide, and making a huge contribution toward better understanding various wildlife populations.
Tip 1
Sentinel's on-site data processing capabilities
While Conservation X Labs' Sentinel processes trail camera and acoustic data on-site to deliver 100,000 insights for about 80 species, efficiently streamlining decision-making processes within conservation efforts globally, Wildlife Insights handles camera trap data with machine learning models, improving the overall efficacy of these initiatives, further highlighting the scalability of such tech from budget-friendly NGO options to government-scale systems. This is despite issues like complex interfaces that continue to exist occasionally in their usage scenarios today.