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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PhD student at Stanford University studying marine migratory species and human-wildlife interactions through biologging, remote sensing, and participatory science.
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Passionate wildlife researcher dedicated to uncovering the secrets of the natural world via the lens of camera traps. With a sharp eye for detail and a strong commitment to wildlife conservation.
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DrivenData
Lead Data Scientist and developer of zamba, a tool for automatic species classification from camera traps
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Technical Specialist at FFI: loves data management, maps, remote sensing & GIS for conservation
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University College London (UCL)
PhD Student at UCL's People and Nature Lab. Studying human-livestock-wildlife coexistence in the Greater Maasai Mara Ecosystem, Kenya.
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Gabriela A. Valencia-Macias, B.Sc. (Universidad Veracruzana), is achieving a master's degree in science at the Ecology Institute (INECOL A.C). She is Colombian-Mexican and has focused her studies on the conservation and biodiversity of amphibians.
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Article
Jacqueline Ramos explains how artificial intelligence can help to track and prevent chimpanzee trafficking across the globe.
6 February 2019
Article
The Open Data Institute and the Office for AI are partnering to explore how data trusts could help to solve environmental, societal and industry challenges by enabling increased access to data while retaining trust....
31 January 2019
Funding
The Ecosulis Rewilding Tech Challenge
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Machine learning is widely recognized as the solution to camera trap data processing, but a user-friendly and broadly-accessible system for putting this tech to use has not yet been developed. In this case study,...
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27 July 2018
Funding
$90K in grants from the Con X Tech Prize
WILDLABS Admin
Looking to prototype or pilot a new conservation tech idea or approach? Conservation X Labs is running an idea competition for teams to create a first draft (i.e. prototype) of their conservation solution. 20 finalists...
11 June 2018
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HWC Tech Challenge: Thermopile Sensor Project
Arribada Initiative
Conflict between humans and wildlife is increasing as human communities expand and wild habitats are destroyed, prompting need for new mitigation techniques. As a winner of the Human Wildlife Conflict Tech Challenge,...
19 April 2018
Article
#Tech4Wildlife Photo Challenge 2018: Our Top 10
WILDLABS Team
Hundreds of people joined our #Tech4Wildlife photo challenge this year, showcasing all the incredible ways tech is being used to support wildlife conservation. We've seen proximity loggers on Tasmanian Devils in...
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Congratulations to Zoohackathon winners, team ODINN!
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| We just wanted to share this news outside the core robotics community - hoping to connect more with conservationists, researchers,... |
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AI for Conservation, Drones | 6 months ago | |
| Hi Lucie @luciegallegos ,Great to see ecoSecrets and happy to collaborate in any way I can! All EcoAssist's models are open-source, and the inference code too. With regards to... |
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Software Development, AI for Conservation, Camera Traps | 6 months ago | |
| Another question. Right now pretty much all camera traps trigger on either PIR sensors or small AI models. Small AI models would tend to have a limitation that they would... |
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AI for Conservation, Camera Traps, Data management and processing tools, Open Source Solutions, Software Development | 6 months ago | |
| Hi Lucille,Thank you for your reply! We’d be really interested in learning more about your developments. We’ll contact you soon to arrange a discussion.Thank you.Best regards,... |
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Acoustics, AI for Conservation, Sensors | 6 months 1 week ago | |
| Hi Lorenzo,I highly recommend the OpenSoundscapes package (developed by the Kitzes Lab at U Pittsburgh) - there are workflows to build your own CNNs there, the documentation is... |
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Acoustics, AI for Conservation, Animal Movement, Open Source Solutions | 6 months 1 week ago | |
| This is probably seen a bit as "self-branding" which I hope is alright, otherwise please let me know! I have spent the past few months... |
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AI for Conservation | 6 months 1 week ago | |
| We are putting together a special issue in the journal Ostrich: Journal of African Ornithology and are welcoming (review) papers on the use of AI in bird research. https://www.... |
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AI for Conservation, Software Development, Citizen Science, Data management and processing tools | 6 months 1 week ago | |
| Hi Adrien,Submissions are open for the special addition. Please email David Ehlers Smith - david.ehlers.smith@birdlife.org.za for more details. We are also soliciting reviewers.... |
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AI for Conservation | 6 months 1 week ago | |
| Hello everyone!During my master thesis in engineering (past autumn), I developed Machine Learning for anti-poaching. As such, I recorded a... |
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Acoustics, AI for Conservation, Data management and processing tools | 6 months 1 week ago | |
| Hey everyone! We’re Deep Voice Foundation, a non-profit using AI to help conserve marine wildlife. We develop acoustic... |
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Acoustics, AI for Conservation | 6 months 2 weeks ago | |
| Hello everyone. My name is Bilal. I recently graduated with a degree in bioengineering and hold a bachelor's degree in computer science,... |
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AI for Conservation, Animal Movement, Human-Wildlife Coexistence, Marine Conservation | 7 months ago | |
| Hey, please find here a dataset about nocturnal bird calls in Europe |
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Acoustics, AI for Conservation, Software Development | 7 months ago |
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ISO Speakers for Emerging Technologies class.
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Carly, that would be great! Thanks! I work with soundscapes and love the work of Rainforest Connection! I'll send you an email (@CUNY) to coordinate!
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Hi Donya! You might check out the Conservation Tech Directory to see what projects/organizations/tools best align with your interests and skills.
Director of Research
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and 1 more
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1 May 2023 5:36pm
5 May 2023 6:15pm
That sounds like a really neat project! Do fish get re-caught often enough that individual ID is useful? Is sample bias (more data from popular spots) an issue?
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Looking to contribute
27 April 2023 2:41am
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31 May 2023 10:21pm
Definitely interested! I'm in the ecoacoustics/acoustic monitoring space, working at Rainforest Connection and Arbimon.