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!
- @womble
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AI Researcher, with 30+ years experience in academia and industry. Currently consulting for a company using drone imagery to analyse property heat loss. Expertise in machine learning, NLP, python, Google Cloud. https://julianrichardson.net
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I am a herpetologist interested in bioacoustics, evolution and conservation biology. Currently, I am a postdoc fellow at Universidade Federal de Santa Maria (UFSM), Brazil.
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- @Harsha
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I am a marine biologist / acoustic ecologist from Australia. Fascinated by bioacoustics, I always look forward to learning from people in conservation!
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Holder of BSc in Applied Zoology. Assistant Ecologist at Ruaha National park.


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University of Zurich
PhD student at the University of Zürich (CH) in PopEcol group, working with camera traps and mammals
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- @fsattar
- | Farook
Farook Sattar received his Technical Licentiate and PhD degrees from Lund University, Sweden. He obtained his B.Eng and M.Eng degrees from Bangladesh University of Engineering & Technology (BUET), Dhaka in Electrical and Electronics Engineering.
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- @LucyD
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Software developer and wildlife ecologist

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- @sroilo
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- @nabilla.nuril
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University College London (UCL)
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- @sarah_dalrymple
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Royal Society for the Protection of Birds (RSPB)

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Article
SPARROW: Solar-Powered Acoustics and Remote Recording Observation Watch
18 December 2024
Comments on Reynolds, S.A et all (2024) 'The potential for AI to revolutionize conservation: a horizon scan'. A very interesting read, perhaps more for the discussion on negative effects of AI and consequences for the...
18 December 2024
The Department of Wildlife, Fish, and Environmental Studies (WFE), SLU, Umeå, is looking for a postdoc with strong interests in wildlife conservation technology. She/he will work within Big Picture, a European project...
18 December 2024
Fully funded 2 year position within a Biodiversa+ funded project
16 December 2024
Develop state-of-the-art interactive ML-based tools for biodiverstiy conservation and related applications
11 December 2024
Join the San Diego Zoo Wildlife Alliance as a Postdoctoral Fellow! Lead groundbreaking bioacoustic and ML research to conserve burrowing owls in SoCal.
26 November 2024
The paper looks at technology advances for vegetation cover changes monitoring. For example, computer vision methods to infer 3D parameters via contextual learning from optical images.
25 November 2024
Interesting webinar on the use of advanced technologies(e.g. Artificial Intelligence, cloud computing, drones, camera traps and satellites) for biodiversity monitoring in the Amazon. Also available in Spanish.
25 November 2024
Careers
We are hiring a computer vision developer at the University of Florida!
20 November 2024
Dive into meaningful play with FathomVerse!
20 November 2024
1 year research role working on the FrogID citizen science project
13 November 2024
Are you stuck on an AI or ML challenge in your conservation work? Apply now for the chance to receive tailored expert advice from data scientists! The deadline for applications is Monday 9 December 2024.
13 November 2024
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Description | Activity | Replies | Groups | Updated |
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Hi everyone! We were so delighted to have Adrien along to our June Variety Hour to share more about the Nocturnal Bird Migration project. If you missed it, you can catch up with... |
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AI for Conservation | 1 year 10 months ago | |
During Andrew's talk in our June Variety hour (see here), @dmorris put out a call in the chat that might be relevant to our marine and ai... |
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AI for Conservation, Marine Conservation | 1 year 10 months ago | |
During Andrew's talk, @dmorris put out a call in the chat that might be relevant to folks catching up on the video, so I'll drop it here too: Re: Andrew's fish work... part... |
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AI for Conservation, Camera Traps, Drones, Marine Conservation | 1 year 10 months ago | |
Thanks, @pvlun,@pvlun we are going to try it to develop a model for feral cat and rat detection in camera trap. |
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AI for Conservation | 1 year 10 months ago | |
A new COST action has been announced which will focus on the use of computer vision for monitoring insects.InsectAI will run for 4 years... |
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AI for Conservation, Autonomous Camera Traps for Insects, Camera Traps | 1 year 10 months ago | |
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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Acoustics, AI for Conservation, Conservation Tech Training and Education, Drones, eDNA & Genomics, Emerging Tech, Geospatial | 1 year 11 months ago | |
Hi Donya! You might check out the Conservation Tech Directory to see what projects/organizations/tools best align with your interests and skills. |
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Acoustics, AI for Conservation, Camera Traps, Drones | 1 year 11 months ago | |
Hey everyone, I am super excited to share two announcements with the Community!🏆🌍 Our flagship Data4Good project - Mbaza AI... |
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AI for Conservation, Camera Traps | 2 years ago | |
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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AI for Conservation, Citizen Science, Software Development | 2 years ago | |
Hi everybody 👋🏽,I'm a UX designer, and I design interfaces and improve user experiences/flows. I would love to contribute to conservation... |
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AI for Conservation, Conservation Tech Training and Education, Emerging Tech, Human-Wildlife Conflict | 2 years ago | |
greetings! i sent you a PM regarding this, feel free to contact me however is most convenient for you - regards,chris |
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Acoustics, AI for Conservation, Camera Traps, Climate Change, East Africa Community, Wildlife Crime | 2 years ago | |
I'm looking for any recommendations for any entry level/internship remote roles/companies in the United States that are focused in... |
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AI for Conservation, Conservation Tech Training and Education, Early Career, Geospatial | 2 years 1 month ago |
Introductions
10 December 2015 8:13pm
17 January 2016 9:08pm
Hi,
I am jason Holmberg from WildMe.org. I am one of the developers of Wildbook (wildbook.org), an open source data management platform for wildlife research. I'm using ML as part of the IBEIS.org project to boost and metascore multiple computer vision algorithms for individual humpback and sperm whales. David, I would love to speak offline if you have the time: jason@wildme.org.
Cheers,
Jason
Google Releases Tensor Flow
18 November 2015 12:10am
20 December 2015 7:05pm
"TensorFlow, you see, deals in a form of AI called deep learning. With deep learning, you teach systems to perform tasks such as recognizing images, identifying spoken words, and even understanding natural language by feeding data into vast neural networks. "
Would this be applicable to an acoustic monitoring network? For example. my research has shown tigers have unique, identifiable vocalizations down to the individual and sex. If this software is applied to my recording network for tigers, would it be able to automatically recognize and categorize these individuals?
For example: when it hears Tiger 108, it would know and then input that it heard Tiger 108 at a particular time and date.
11 January 2016 12:38pm
The catch will be (and for any neural network or AI type learning I would expect the same) the training phase. If you are able to tell the sounds apart or identify a specific sound as belonging to a certain individual, the AI should afterwards be able to automatically identify the critical factors needed to distinguish the voices of the individuals. But it will need enough input from each individual as well as the different vocalizations used by tigers. AFAIKT it will be able to do this automatically afterwards, but I am not sure if (a) you will get enough identifiable vocalisations and (b) with a wide enough range of typical tiger vocalisations for it to be really reliable. Training on zoo animals might work? I am also interested in this, but for jackals instead of tigers.
11 January 2016 2:30pm
I'd like to suggest our open source package Wildbook (http://www.wildbook.org) as a base data management platfor for this. I agree with the above that there are a number of challenges around the vocalizations themselves, but having the identity information in a good database and data model is a great foundation. That's what we're doing for our computer vision/deep learning project at www.IBEIS.org.
Our non-profit WildMe.org is running both. Feel free to contact us with questions. We have played with time series matching (often used for speech recognition)...but actually for whale flukes. Would be happy to discuss potential for audio ID.
Deep Learning Image Recognition of Species In Global Wildlife Crime Reporting
31 December 2015 7:28pm
Big Data and Conservation: Deluge or Drought?
22 December 2015 12:00am
Cheap Space, DIY Imaging and Big Data
21 December 2015 12:00am
The Impact of the Internet of Things
10 December 2015 12:00am
Harnessing Big Data to Combat Illegal Wildlife, Timber and Fisheries Trade

26 November 2015 12:00am
Technology for Traceability

26 November 2015 12:00am
From Data Collection to Decisions
6 November 2015 12:00am
The Social Lives of Conservation Technologies and Why They Matter
2 November 2015 12:00am
10 December 2015 8:41pm
To start things off...
I'm David J Klein. My background is in deep learning, machine learning, neuroscience, neuromorphic computing, and signal processing. I've been doing the startup thing Silicon Valley for the last 11 years after being in academia for a while. I've worked on products ranging from speech recognition systems, to cloud-based deep learning platforms. These days, some use the blanket term "AI".
For the last several years I've been developing software for Conservation Metrics which gives their analysists the ability to use deep learning to process large volumes of audio and image data from remote sensors in order to monitor population density changes of endangered species, detect collisions of birds and bats with infrastructure, and find rare and elusive species.
More broadly, I'm interested in integrating many disparate sensing domains from eDNA, to land-based sensors, to GIS data in order to provide tools to conservation scientists and ecologists that will enable them to develop a higher resolution understanding of the health of ecosysems around the globe and their response to positive or negative human interventions.
I'm looking forward to interacting with you all. Please let me know what other questions you have for me, and other ways I can help.
Regards,
David