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!
An enthusiastic technology conservationist!
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Entrepreneur and investor in African SMEs
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- @Tjomme
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Building a community of AI professionals working on the Sustainable Development Goals.
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World Wide Fund for Nature/ World Wildlife Fund (WWF)
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- @nora.gourmelon
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PhD candidate in Computer Science working on Computer Vision for glacier front delineation in synthetic aperture radar satellite images
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Zoological Society London (ZSL)
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- @jsevans
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Senior biometrician, with the Nature Conservancy science team, attempting to bring vigor from diverse fields such as landscape ecology, spatial statistics, remote sensing and applied mathematics to answer practical conservation questions.
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- @StreamingScience
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Georgia Institute of Technology
Andrew’s always looking to find new interdisciplinary teams in the conservation tech space. He is a postdoctoral researcher at Max Planck Institute, who completed his PhD at Georgia Tech in 2022. His interests including conservation tech education and engineering work.
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Max Planck Institute of Animal Behavior (MPI-AB), Technical University of Munich (TUM)
Behavioral Ecologist
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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.
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Catch up on the conservation tech discussions and events that happened during World Wildlife Day 2024!
7 March 2024
EcoAssist introduces a free African species identification model for camera trap images, capable of recognising 30 species.
5 March 2024
Join us to help prevent biodiversity loss! Understory is hiring a postdoc to lead R&D Development on generalizing Computer Vision models for vegetation identification across space/time/phenotypes.
29 February 2024
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Description | Activity | Replies | Groups | Updated |
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Thank you @carlybatist , @Freaklabs and @MK . The inputs are very useful and I am progressing on my project based on that. Appreciate a lot. |
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Acoustics, AI for Conservation | 1 year 11 months ago | |
Some folks doing work in this space - Wildlife Drones, Conservation Drones, UAV Wild, AfricanDrones, Oceans Unmanned, Geonadir. |
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Drones, AI for Conservation, Citizen Science, eDNA & Genomics, Emerging Tech | 1 year 11 months ago | |
Dear Community,Together with Hackster.io, Seeed Studio is very happy to jointly organize “IoT Into the Wild Contest for Sustainable Plant... |
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AI for Conservation, Connectivity, Emerging Tech, Open Source Solutions, Sensors | 1 year 11 months ago | |
Thanks Carly. No special areas of interest for now although that will happen over time. Thanks so much for your reply. I will check the Conservation Tech directory out. Soumya |
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AI for Conservation | 1 year 11 months ago | |
Fascinating article, combining machine learning and acoustical signals to correlate coral reef health.https://www.sciencedirect.com/science... |
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Acoustics, AI for Conservation, Marine Conservation | 2 years ago | |
We've now wrapped our first run of AI for Conservation Office Hours and you can read my review of how it went and lessons learned here. Given the ... |
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AI for Conservation | 2 years 5 months ago | |
Hi everyone! We are spreading the word about a free, open-source tool called Zamba that automatically detects and... |
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AI for Conservation | 2 years 6 months ago | |
Hi Wildlabbers, This week's Tech Tutor Jamie MacAulay is talking about how to use and analyze large acoustic data using... |
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Acoustics, AI for Conservation, Marine Conservation | 2 years 7 months ago | |
Hi Wildlabbers, We're getting ready for tomorrow's episode with Tech Tutor Lily Xu, who'll talk to us about how machine... |
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AI for Conservation, Protected Area Management Tools, Wildlife Crime | 2 years 9 months ago | |
Looks good, but what is the added value compared to other examples as Obsidentify and Plantnet? |
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AI for Conservation | 2 years 9 months ago | |
https://www.dryad.netJob description"Dryad is an environmental IoT startup based in Berlin-Brandenburg. Our mission is to develop a large-... |
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AI for Conservation | 2 years 9 months ago | |
Deep Learning Engineer at Pachama - https://jobs.lever.co/pachama/81716dd9-8019-4916-add2-fcfaae426331 Embedded Software Engineer... |
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AI for Conservation | 2 years 9 months ago |