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!
Natural Solutions
Computational ecologist - Engineer at Natural Solutions (France)



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- @Lucille
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La Trobe University
Marine bioacoustician and elasmobranch scientist
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- @KMucha
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Species360
Senior Product Owner of ZIMS for Studbooks and the SCTI Toolkit at Species360

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- @sam.cope.king
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ProtectedSeas
Marine Monitor (M2) Senior Scientist


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Ol Pejeta Conservancy
Endeavoring to implement tech solutions for conservation.



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- @ppebs
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Primatologist who studies human-primate coexistence and self-medicative behavior in non-human primates
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- @sarange_angwenyi
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Wildlife veterinarian and researcher working across Kenya. Currently leveraging technology for wildlife disease surveillance.
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University of Suffolk
Sustainability Researcher • Environmental Data Scientist & Technologist • Earth Scientist
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- @varshasuresh
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Program Officer & Researcher at Foundations of Success

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- @tutgut5
- | she/her
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Description | Activity | Replies | Groups | Updated |
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MIT has this Moo Deng-based fun challenge! More seriously it relates to AI and human-nature interaction. I imagine people on Wildlabs would... |
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AI for Conservation | 1 day ago | |
Hi Ethan, It's indeed a competitive area. My advice for you (and anybody else seeking a PhD supervisor)...Do background research on each individual potential supervisor and always... |
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Early Career, AI for Conservation, Animal Movement, Climate Change | 4 days 9 hours ago | |
Hi Nick,At Wildlife.ai, from the other side of the world, we would be happy to chat with you. PM if interested Victor |
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AI for Conservation, Emerging Tech | 2 days 11 hours ago | |
Hi everyone,What should we share or demo about Software Quality Assurance? Alex Saunders and I, the two Software QA people at Wildlife Protection Solutions (WPS) are going to... |
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Software Development, AI for Conservation, Open Source Solutions | 4 days 4 hours ago | |
My name is Frank Short and I am a PhD Candidate at Boston University in Biological Anthropology. I am currently doing fieldwork in Indonesia using machine-learning powered passive... |
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Acoustics, AI for Conservation, Animal Movement, Data management and processing tools, Early Career, Emerging Tech, Ethics of Conservation Tech, Protected Area Management Tools, Software Development | 2 weeks 1 day ago | |
This looks like a great application, thank you! I wonder if they are planning to run this study in future years. |
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AI for Conservation | 2 weeks 3 days ago | |
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Latin America Community, Acoustics, AI for Conservation, Camera Traps, Drones, Early Career | 2 weeks 6 days ago | ||
@LukeD, I am looping in @Kamalama997 from the TRAPPER team who is working on porting MegaDetector and other models to RPi with the AI HAT+. Kamil will have more specific questions. |
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AI for Conservation, Camera Traps | 3 weeks ago | |
Super happy to finally have Animal Detect ready for people to use. We are open for any feedback and hope to bring more convenient tools :) |
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AI for Conservation | 3 weeks ago | |
Hi Ștefan! In my current case, I am trying to detect and count Arctic fox pups. Unfortunately, Arctic fox does not seem to be included in the training data of SpeciesNet but... |
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AI for Conservation, Camera Traps | 3 weeks 1 day ago | |
Interesting. Thanks for the explanation. Nice to hear your passion showing through. |
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AI for Conservation, Camera Traps, Data management and processing tools, Open Source Solutions, Software Development | 3 weeks 3 days ago | |
📸 Do you use camera traps in your work? Take part in our survey!Hi everyone! I’m currently a final-year engineering... |
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Camera Traps, AI for Conservation, Data management and processing tools, Open Source Solutions, Software Development | 3 weeks 4 days ago |
Hello there
1 July 2022 5:00pm
Intro webinar - The Biodiversity Digital Twin: a new solution to support protection & restoration of ecosystems
30 June 2022 1:22am
New Conservation Tech Directory update
27 June 2022 4:45pm
Live Q&A on AI models to process Camera Trap Imagery: All about WildID
21 June 2022 6:49am
23 June 2022 11:43am
Thank you so much Kate for the excellent answers, explanations, insights and pointers; This was nothing short of Amazing!
Thank you all for joining us in this discussion; I hope this has been helpful and you now have a solution for processing your 1 million + camera trap imagery. If you have any questions for Kate, please feel free to drop them in this discussion thread- she is more than happy to answer. If you’d like to reach out to Kate directly, you can Direct message her here or send her an email at: support@wildid.app
Thank you!
23 June 2022 11:45am
Thank you so much Netty, I really enjoyed it.
Good luck to you all with your work.
Keep well!
Live Q&A session on AI models for Processing Camera Trap Imagery:A highlight of WildID.
22 June 2022 1:42pm
Bird Acoustic Solution
9 June 2022 11:31pm
11 June 2022 1:16pm
There are a bunch of different options for detecting calls in audio data, from proper statistical platforms such as R/Python, to bespoke software such as Arbimon, Kaleidoscope & Raven. Edge Impulse also an online ML model-building interface, but this is more focused on then deploying the models onto devices for edge computing. Arbimon has template matching features that are a good way to start finding detections to build a training dataset, I have used it for this in the past. Arbimon is online & free. Kaleidoscope has a clustering function which is again a good first step to start picking out the low-hanging fruit of detections so to speak. It's a desktop app, but this is not free ($400/yr). Raven also has some automated features - template & band-limited entropy detectors. It's also a desktop app and not free ($100-$800 depending on 1-year or permanent license and whether non-profit or not; not sure where a government agency would fit into that).
There is always the ubiquitous split between biologists who traditionally are taught to use R and tech/computer folks who are taught to use Python, but for ML, Python's ecosystem is really well set up. Not sure what the level of programming you/your dept has, but there are a TON of free resources online for learning it if you were interested.
Relevant Python bioacoustics packages potentially of use - Acoustic_Indices, scikit-maad, Ketos, OpenSoundscape (as well as the obvious ML ones such as TensorFlow)
Some R packages as well - soundecology, bioacoustics, monitoR, warbleR, gibbonR
@tessa_rhinehart has created a fabulous list of bioacoustics software that you can find here: https://github.com/rhine3/bioacoustics-software.
You can also turn to articles that have already done similar things and reach out to the authors to discuss their methods. I've got a (totally un-exhaustive) list of papers on passive acoustic monitoring, with a section on 'analyses' that you might find useful to start with; I can email it to you if you'd like. Working on a PAM training materials page on my website that it will be available at shortly as well (will post the link to Wildlabs when it's live!).
Hope this is helpful!
16 June 2022 9:27am
Hi,
Look at this publication (below) and download the BirdNet app. The computer code is provided to train ML algorithm that will allow you to tailor the model with your own data.
Thanks, Mrigesh
20 June 2022 1:00am
Thank you @carlybatist , @Freaklabs and @MK . The inputs are very useful and I am progressing on my project based on that. Appreciate a lot.
Cofounder needed
9 June 2022 4:23pm
17 June 2022 1:14pm
What about developing a drone conservation training course for field conservation staff teaching specific skills for specific research needs.
17 June 2022 6:54pm
How exciting @Joyeeta ! I'd love to learn more about the companies and projects you worked on, can you share more info about them?
I once chatted to an entrepreneurial advisor with a couple of my conservation tech ideas, and he said my ideas are good/impactful but don't make for a product worth millions of $$$ of turnover per year that would interest investors. So I am very curious about how you got your conservation tech businesses off the ground!
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Some folks doing work in this space - Wildlife Drones, Conservation Drones, UAV Wild, AfricanDrones, Oceans Unmanned, Geonadir.
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Nothing too much more to share about WildID - I think you've had an earful already! But just to say that we really do enjoy working with our users, so don't be shy to get in touch for any questions, or think you would be bothering us if you need support. We're excited to bring more projects on board and extend our training sets to new locations, camera types and species.
For those in regions outside Africa, we are considering releasing a version of WildID that uses MegaDetector from Microsoft AI - so it will classify your images into empties, and then human, vehicle and animal (just those three classes). You would then be able to define your own species list, and edit the animal pictures to the correct species. Still a fair amount of work for you to edit, but you are probably doing the work already, and at least you would have an easy interface in which to do it, and particularly empties excluded already for you. Get in touch with us if this would be of use to you.