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• Tiger, Tiger, in the Night... Now Visible in Real Time

Press Release for International Tiger Day – July 29th, 2022: For the first time ever, wild tigers and their prey have been detected by AI-powered, cryptic cameras that transmit the images to the cell phones and computers of park managers. Just as important, the elapsed time from the motion sensor triggered by the passing tiger, to running the AI, to transmission to the cell network, to the Internet, and to the end user is less than 30 seconds, making this technology a true real-time system.

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• CERES TAG

Ceres Tag sends just in time alerts and GPS location to have the power to track and trace.

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• New papers on passive acoustic monitoring

PAM & transfer learning, defining occupancy in surveys, effects of anthropogenic noise on fish, soundscapes to track ecosystem recovery, detecting sharks with echosounders, using PAMGuard to detect marine mammals 

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• New paper: Predicting poaching hotspots in the largest remnant of the Atlantic Forest by combining passive acoustic monitoring & occupancy models  

Julia Martínez Pardo et al., Published in Biological Conservation

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• CERES TAG

Ceres Tag sends just in time alerts and GPS location to have the power to track and trace.

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• Introducing WILDBEAR Awardee Alyssa Bohart

Get to know Alyssa Bohart, our first WILDBEAR Award recipient, who works with GPS-collared bears in Canada.

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• Bird Sounds Global web portal

A new web portal for annotating bird sounds has been opened called Bird Sounds Global (BSG). It is part of project LIFEPLAN, and its key objective is to develop global, automated software for bird sound identification.

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• Identification of Wildlife in Camera Trap Images

<p>Camera trap wildlife surveys can generate vast amounts of imagery. A key problem in the wildlife ecology field is that vast amounts of time is spent reviewing this imagery to identify the species detected. Valuable resources are wasted, and the scale of studies is limited by this review process. The use of computer software capable of extracting false positives, automatically identifying animals detected and sorting imagery could greatly increase efficiency. AI has been demonstrated as an effective option for automatically identifying species from camera trap imagery. Currently available code bases are inaccessible to the majority of users; requiring high-performance computers, advanced software engineering skills and, often, high-bandwidth internet connections to access cloud services. The <em>ClassifyMe</em> software tool is designed to address this gap and provides users the opportunity to utilise state-of-the-art image recognition algorithms without the need for specialised computer programming skills. <em>ClassifyMe</em> is IDEAL for field researchers, allowing users to sweep through camera trap imagery using field computers instead of office-based workstations.</p>

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• The Foes and Floes of Labelling Aerial Pictures Manually

This WhaleSeeker article discusses how reliable distribution data depends on accurate labelling from survey images, and how AI can improve this process.

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• Human-wildlife conflict one of the greatest threats to wildlife species - WWF and UNEP report

Report says the problem is as much a development and humanitarian issue as a conservation concern and risks derailing the Sustainable Development Goals.

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• News: The Latest in Conservation Tech

<p>Check out this round-up of three of the latest news stories from the conservation tech world. </p> <p><a href="https://wildlabs.us11.list-manage.com/subscribe/post?u=13a5323dc43234ee66d95cc90&id=fce1034265">See more conservation tech news by subscribing to our bi-monthly digest. </a></p>