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!
In Ellie Warren's interview with Sara Beery as part of the Technical Difficulties Editorial Series, they discussed how the hype surrounding machine learning impacts our perceptions of failure, and how conservationists...
23 November 2021
CAIMAN is a product from the Sensing Clues Foundation that automatically classifies animals on images from camera traps. It aims to be available by the end of 2021, contact the Sensing Clues team for more details. This...
18 November 2021
The GEO-Microsoft Planetary Computer Programme invites the GEO community to be among the early adopters of Microsoft's Planetary Computer. The Programme will support a number of 12-month projects that use The Planetary...
4 November 2021
On 3rd November 2021, Earthranger Announced Giraffe Conservation Foundation and Lion Guardians as the inaugral Conservation Tech Award Recipients. The two organizations are Harnessing the Power of Technology to Protect...
3 November 2021
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The Centre for Statistics in Ecology, Environment and Conservation, a research group within the Department of Statistical Sciences at the University of Cape Town, is now hiring for a funded postdoc or PhD postion with...
1 November 2021
This article explores the use of IoT and Machine Learning Technologies in Ewaso Nyiro River, Kenya - which serves several communities as well as wildlife in Olpejeta Conservancy and Lewa Conservancy, among others. Data...
21 October 2021
The International Journal of Computer Vision is calling for papers on Computer Vision Approach for Animal Tracking and Modeling. Visit the Springer website for further details and submission guidelines.
20 September 2021
In this thought piece from Whale Seeker, Malcolm Kennedy considers the strengths of weaknesses of citizen science and AI, both used to analyze large amounts of conservation data, and discusses the importance of data...
19 August 2021
Today, we're chatting with our WILDLABS Fellowship: On the Edge partners at Edge Impulse about how conservation tech funding and support can be more sustainable, and why reimagining how fellowships make an impact is so...
13 August 2021
To celebrate our newly-lauched WILDLABS Fellowship: On the Edge, I spoke with the Edge Impulse team about why uniting the conservation and tech worlds to make funding, tools, training, and support accessible and...
9 August 2021
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Wildlife Insights is excited to announce the public release of their new platform! Read on to learn about all the useful features you'll find on Wildlife Insights, and check out WILDLABS' Tech Tutors episode with...
27 July 2021
Our friends at BearID joined an EXPLORE.org live chat to discuss their work identifying the bears of Katmai National Park with powerful AI technology. Watch the full panel event below, or here on EXPLORE.org's Youtube...
1 July 2021
August 2023
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Imageomics Institute Image Datapalooza, August 2023
2 June 2023 11:44pm
ISO Speakers for Emerging Technologies class.
31 May 2023 4:29pm
2 June 2023 2:08pm
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!
10 AI for the Planet Projects you should be excited about
25 May 2023 11:07am
Looking for AI volunteer positions
24 May 2023 5:41am
24 May 2023 3:45pm
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
Mbaza AI recognized by UNESCO & new team member
17 May 2023 8:49pm
Happywhale: AI-Powered Whale Identification

16 May 2023 10:00am
Lecturer/Associate Professor of Ecology and Innovative Technologies

16 May 2023 9:25am
Applications Now Open: Conservation Tech Award
15 May 2023 10:21pm
Photo Quadrats, AI, and MERMAID: A Case Study from Mozambique
12 May 2023 3:44pm
AI for Conservation Office Hours: 2023 Review

11 May 2023 10:00am
Crowdsourcing individual ID for pop dyn?
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?
GRO is the story of what on Earth is going on
5 May 2023 1:50pm
Using computer vision to understand bee vision
5 May 2023 1:10am
Here's an innovative project from the Harvey Mudd College Bee Lab that could help us understand how bees view their environments, and thus better protect bee habitat. This project uses computer vision and drone imagery to replicate "bee vision" of flowers and how it differs from a human's view of the same habitat.
Electrical Engineer (Remote)
2 May 2023 8:45pm
Full Stack Python Developer (Remote)
2 May 2023 8:40pm
How can you tell if a photo is AI generated? Here are some tips.
29 April 2023 3:35pm
EarthRanger User Conference
27 April 2023 5:52am
Looking to contribute
27 April 2023 2:41am
Artificial Intelligence and Conservation: Closing Session
26 April 2023 8:54pm
Artificial Intelligence and Conservation with Lily Xu
26 April 2023 8:41pm
WWF's recent Fuller Seminar Series on Artificial Intelligence and Conservation featured some familiar faces from the WILDLABS community, including our past Tech Tutor Lily Xu! Check out her presentation talking about AI-based causal reasoning and how it can be applied to conservation challenges.
AI Animal Identification Models
30 March 2023 5:01am
20 April 2023 12:53am
Thanks Dan, that is very helpful. No zebras here but I did see four deer wandering through the streets this morning. Quite wild at times here!
I am totally willing to try an image classifier if it reports multiple objects it identifies in a scene. I will give this a go.
I think 1 fps would be quite acceptable actually, and in some perspective actually advantageous in reducing how much data is getting logged.
I tried upgrading my existing object detector model to YOLOv8 following the links you sent, but I don't think it is possible to upgrade the model on the framework I'm using (ml5js) so I think I will have to try a different framework.
Thank you.
25 April 2023 2:08pm
Hi David
It appears that you have been looking for existing models, however, most existing models are trained on either COCO or some other very generic dataset. So, if you want to identify just animals, you may be better off training your own model. It seems no one in this thread mentioned yet that it is possible to do transfer learning on existing models, which keeps most of the "visual part" of the model as is, but just changes the classification part so it can identify other things. This way you can take an existing model trained on COCO and in a fraction of the time it takes to train a full model, just retrain that for your animals.
Also have a look at your requirements for the inferencing stage. Some models take long in training but are superfast in inference and others are slow in both cases but very accurate, etc. If you want semi-realtime inferencing, you are probably looking at single shot detectors (SSD), and not RCNNs.
26 April 2023 7:34pm
Thanks Bas! I'll look into SSD vs RCNNs, I'd never heard of an SSD.
Feathered forecast: Tech tools comb weather data for bird migrations
26 April 2023 2:50pm
Since its launch in 1999, the BirdCast project has used weather radar data to track and forecast bird migrations across the U.S. In recent years, technology such as cloud computing and machine learning have helped make the work of researchers in the project easier and more automated. The BirdCast project is now working on integrating radar data with human observations and bioacoustics to help identify the bird species traversing the skies.
Congo Basin activity?
30 March 2023 9:14pm
25 April 2023 5:08pm
greetings!
i sent you a PM regarding this, feel free to contact me however is most convenient for you -
regards,
chris
Looking for entry level remote role in GIS/environmental analysis in the United States
22 April 2023 12:05am
Catch up with The Variety Hour: April
21 April 2023 10:42am
Call for survey participants (AI/ML practitioners)
19 April 2023 3:17pm
Camera traps, AI, and Ecology
14 April 2023 10:08am
19 April 2023 9:48am
Segment Anything
13 April 2023 9:16pm
Our lead engineer just shared this tool for segmenting images and we're excited to test it out on our fishy & underwater pix. Has anyone else used it?
31 May 2023 10:21pm
Definitely interested! I'm in the ecoacoustics/acoustic monitoring space, working at Rainforest Connection and Arbimon.