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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Review by Professor Iain H Woodhouse
29 April 2024
Careers
The Smithsonian National Zoo & Conservation Biology Institute is seeking a Program Manager to help coordinate multiple organizations in an effort to integrate movement data & camera trap data with global...
22 April 2024
The Smithsonian National Zoo & Conservation Biology Institute is seeking a Postdoctoral Research Fellow to help us integrate movement data & camera trap data with global conservation policy.
22 April 2024
Join the Seeed Vision Challenge, an opportunity for conservation innovators to harness the power of AI vision sensors for environmental monitoring and protection.
10 April 2024
Full-Stack Software Developer (Python/React) - Specializing in AI/ML for Wildlife Conservation
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Article from Ars Technica about how difficult it is to detect and avoid kangaroos...
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Finwave, while currently in beta-testing, is being used to help reunite an orphaned whale with its family.
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18 month postdoc research position, Netherlands, EU-funded
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NASA and IBM have teamed up to create an AI Foundation Model for Earth Observations, using large-scale satellite and remote sensing data, including the Harmonized Landsat and Sentinel-2 (HLS) data.
28 March 2024
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You’re invited to the WILDLABS Variety Hour, a monthly event that connects you to conservation tech's most exciting projects, research, and ideas. We can't wait to bring you a whole new season of speakers and...
22 March 2024
Join our multi-national team at the AI for Biodiversity Change Global Climate Center! We're hiring a Research Data Manager & Tech Coordinator at Ohio State. Support cutting-edge research on climate change &...
15 March 2024
Introducing The Freshwater Sounds Archive, a global database of sounds produced by freshwater species. Submit your species-specific or unidentified sounds to the archive now and receive recognition for your...
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Update: I asked the same question on twitter so I'm sharing answers I got there:
Let's chat! We've been training models to run on trail cameras as images/videos are captured, and have worked on migratory birds along coastlines (more info: https://t.co/NzW4GO2Wqp)
— Henrik Cox (@henrik_cox) June 1, 2022
21 June 2022 5:41pm
Hi Yvan,
I dropped this into the AI for Conservation slack group as well, you got this reply this morning:
Steph
8 August 2022 11:12am
Hi Yvan,
If you find something which reaches your expectation and especially the ability to identify individual with plumage patterns I will be intereted.
In the same idea that Ultralytics, there is :
Lobe · GitHub
Machine Learning Made Easy. Lobe has 11 repositories available. Follow their code on GitHub.
Which could probably answer your first and second requirements.
And find here a great website showing all the IA-based camera software, you may find solutions or contact throw this list:
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Hi Jitendra.
If they are still images, many people are using Megadetector to analyze their images. I'm not sure how it will do in species classification, but it can tell you if there are images of interest in the shots. Others here can probably give you more detailed instructions on how to use it to batch process camera trap images.
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Have you considered creating a Kaggle competition? If you already have lots of images, and some that have been labelled, then this could be a good way to get people working on a solution
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