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 machine learning and drone technology


UoB uses machine learning and drone technology in wildlife conservation

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The University of Bristol (UoB) has partnered with Bristol Zoological Society (BZS) to develop a trailblazing approach to wildlife conservation, harnessing the power of machine learning and drone technology to transform wildlife conservation around the world. Backed by the Cabot Institute for the Environment, BZS and EPSRC's CASCADE grant, a team of researchers travelled to Cameroon in December last year to test a number of drones, sensor technologies and deployment techniques to monitor the critically endangered Kordofan giraffe populations in Bénoué National Park. "There has been significant and drastic decline recently of larger mammals in the park and it is vital that accurate measurements of populations can be established to guide our conservation actions," said Dr Gráinne McCabe, head of field conservation and science at BZS. "Bénoué National Park is very difficult to patrol on foot and large parts are virtually inaccessible, presenting a huge challenge for wildlife monitoring. What's more, the giraffe are very well camouflaged and often found in small, transient groups," said Dr Caspian Johnson, conservation science lecturer at BZS. Striving to uncover the best method for airborne wildlife monitoring, BZS reached out to Dr Matt Watson from the UoB's School of Earth Sciences, and Dr Tom Richardson from the University's Aerospace Department, as well as a member of the Bristol Robotics Laboratory (BRL). The team forged successful collaborations using drones to monitor and measure volcanic emissions to create a system for wildlife monitoring.

  Country: Africa > Cameroon (0.27)