Camera traps have been a key part of the conservation toolkit for decades. Remotely triggered video or still cameras allow researchers and managers to monitor cryptic species, survey populations, and support enforcement responses by documenting illegal activities. Increasingly, machine learning is being implemented to automate the processing of data generated by camera traps.
A recent study published showed that, despite being well-established and widely used tools in conservation, progress in the development of camera traps has plateaued since the emergence of the modern model in the mid-2000s, leaving users struggling with many of the same issues they faced a decade ago. That manufacturer ratings have not improved over time, despite technological advancements, demonstrates the need for a new generation of innovative conservation camera traps. Join this group and explore existing efforts, established needs, and what next-generation camera traps might look like - including the integration of AI for data processing through initiatives like Wildlife Insights and Wild Me.
Group Highlights:
Our past Tech Tutors seasons featured multiple episodes for experienced and new camera trappers. How Do I Repair My Camera Traps? featured WILDLABS members Laure Joanny, Alistair Stewart, and Rob Appleby and featured many troubleshooting and DIY resources for common issues.
For camera trap users looking to incorporate machine learning into the data analysis process, Sara Beery's How do I get started using machine learning for my camera traps? is an incredible resource discussing the user-friendly tool MegaDetector.
And for those who are new to camera trapping, Marcella Kelly's How do I choose the right camera trap(s) based on interests, goals, and species? will help you make important decisions based on factors like species, environment, power, durability, and more.
Finally, for an in-depth conversation on camera trap hardware and software, check out the Camera Traps Virtual Meetup featuring Sara Beery, Roland Kays, and Sam Seccombe.
And while you're here, be sure to stop by the camera trap community's collaborative troubleshooting data bank, where we're compiling common problems with the goal of creating a consistent place to exchange tips and tricks!
Header photo: ACEAA-Conservacion Amazonica
DrivenData
AI for conservation developer
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University of Adelaide
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- @KAugust
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- @lucytallents
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VerdantLearn
Sociable e-learning for conservation capacity building
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- @cshriver
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Georgia Institute of Technology
PhD student in Quantitative Biosciences
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Team lead for the ARISE Biocloud team, developing an infrastructure for biodiversity monitoring and digital species identification. Also, project lead for the Diopsis insect camera project.
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I am a recently graduated Computer Scientist and Mathematician passionate about animals and nature.
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- @aliciamrich
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Assistant Professor studying Primate Molecular Health at Itwara Forest in Uganda and AZA-accredited zoos.
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Conservation International
Wildlife Insights Managing Director
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- @hedwigl
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Work with bioacoustic equipment, management, maintenance and testing, for the Bioacoustic Unit (bioacouistic.abmi.ca).
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