AI for Conservation

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Artificial intelligence is increasingly being used in the field to analyse information collected by wildlife conservationists, from camera trap and satellite images to audio recordings. AI can learn how to identify which photos out of thousands contain rare species; or pinpoint an animal call out of hours of field recordings - hugely reducing the manual labour required to collect vital conservation data.

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With new technologies revolutionizing data collection, wildlife researchers are becoming increasingly able to collect data at much higher volumes than ever before. Now we are facing the challenges of putting this information to use, bringing the science of big data into the conservation arena. With the help of machine learning tools, this area holds immense potential for conservation practices. The applications range from online trafficking alerts to species-specific early warning systems to efficient movement and biodiversity monitoring and beyond.

However, the process of building effective machine learning tools depends upon large amounts of standardized training data, and conservationists currently lack an established system for standardization. How to best develop such a system and incentivize data sharing are questions at the forefront of this work. There are currently multiple AI-based conservation initiatives, including Wildlife Insights and WildBook, that are pioneering applications on this front.

This group is the perfect place to ask all your AI-related questions, no matter your skill level or previous familiarity! You'll find resources, meet other members with similar questions and experts who can answer them, and engage in exciting collaborative opportunities together.

Just getting started with AI in conservation? Check out our introduction tutorial, How Do I Train My First Machine Learning Model? with Daniel Situnayake, and our Virtual Meetup on Big Data. If you're coming from the more technical side of AI/ML, Sara Beery runs an AI for Conservation slack channel that might be of interest. Message her for an invite.

Header Image: Dr Claire Burke / @CBurkeSci

Explore the Basics: AI

Understanding the possibilities for incorporating new technology into your work can feel overwhelming. With so many tools available, so many resources to keep up with, and so many innovative projects happening around the world and in our community, it's easy to lose sight of how and why these new technologies matter, and how they can be practically applied to your projects.

Machine learning has huge potential in conservation tech, and its applications are growing every day! But the tradeoff of that potential is a big learning curve - or so it seems to those starting out with this powerful tool!

To help you explore the potential of AI (and prepare for some of our upcoming AI-themed events!), we've compiled simple, key resources, conversations, and videos to highlight the possibilities:

Three Resources for Beginners:

Everything I know about Machine Learning and Camera Traps, Dan Morris | Resource library, camera traps, machine learning
Using Computer Vision to Protect Endangered Species, Kasim Rafiq | Machine learning, data analysis, big cats
Resource: WildID | WildID

Three Forum Threads for Beginners:

I made an open-source tool to help you sort camera trap images | Petar Gyurov, Camera Traps
Batch / Automated Cloud Processing | Chris Nicolas, Acoustic Monitoring
Looking for help with camera trapping for Jaguars: Software for species ID and database building | Carmina Gutierrez, AI for Conservation

Three Tutorials for Beginners:

How do I get started using machine learning for my camera traps? | Sara Beery, Tech Tutors
How do I train my first machine learning model? | Daniel Situnayake, Tech Tutors
Big Data in Conservation | Dave Thau, Dan Morris, Sarah Davidson, Virtual Meetups

Want to know more about AI, or have your specific machine learning questions answered by experts in the WILDLABS community? Make sure you join the conversation in our AI for Conservation group!

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@sarah_dalrymple
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Royal Society for the Protection of Birds (RSPB)

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Tech Matters

Project Director, Terraso.org (1000 Landscapes for 1 Billion People): open source software for farmers, ranchers & communities.

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CTO of IoSA, the Internet of Small Animals. Creator of ProxLogs

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VerdantLearn

Sociable e-learning for conservation capacity building

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@Benjamin_Barca

NatureMetrics

Passionate conservationist based in Italy, currently focusing on eDNA and impact with NatureMetrics.

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Conservation biologist, executive director at the Tesoro Escondido Reserve Foundation in the Ecuadorian Chocó, working on participatory action research, environmental education, primate and amphibian conservation

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@Erika_Barthelmess

St. Lawrence University

Professor of Biology at St. Lawrence University

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Wildlife Conservation Society (WCS)

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@Edonga
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Paul Edonga is from the Indigenous Pastoralist Tribes of Northern Kenya. A seasoned Leader in indigenous-led conservation of Endangered Beisa Oryx, African Small Antelopes their habitats & Dryland Forests. He's the founder of Save Beisa Oryx Community Resilience Trust-SBOC

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Description	Activity	Groups	Updated
[ARCHIVED] Job: ML developer at Skytruth	Hi folks! The team at Skytruth (responsible for Global Ocean Watch) are looking for a machine learning developer. It might be of...	AI for Conservation	9 years 6 months ago
Introductions	Hi, I am jason Holmberg from WildMe.org. I am one of the developers of Wildbook (wildbook.org), an open source data management platform for wildlife research. I'm...	AI for Conservation	9 years 7 months ago
Google Releases Tensor Flow	I'd like to suggest our open source package Wildbook (http://www.wildbook.org) as a base data management platfor for this. I agree with the above that there are a number of...	AI for Conservation	9 years 7 months ago
Deep Learning Image Recognition of Species In Global Wildlife Crime Reporting	Over the past year the open data GDELT Project (http://gdeltproject.org/), which monitors local news coverage worldwide in...	AI for Conservation	9 years 7 months ago

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