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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BearID Project & Arm
Developing AI and IoT for wildlife
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KONKLUSI (Kolaborasi Inklusi Konservasi - Yayasan)
Your friendly Indo-Crocky-Croc
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Wildlife Protection Solutions (WPS)
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Ocean Science Analytics
Marine mammal ecologist and online technical trainer
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WILDLABS & Fauna & Flora
I'm the Executive Manager at WILDLABS.
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- @Dominik
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PhD Student on bio- and ecoacoustics at the University of Freiburg (GER)
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I am nature lover and now lost the tolerance to just be an admirer watching its destruction. Hence joining this crew to contribute my supportive work much lesser than a penny worth
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- @capreolus
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wildlife biologist with capreolus.at
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- @ryanhuang
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Conservation scientist based in Pretoria, South Africa
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PhD student at the University of Mississippi; research interests include predator/prey dynamics, particularly the landscape of fear in relation to species conservation. Rookie at using arduino
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- @Rob_Appleby
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Wild Spy
Whilst I love everything about WILDLABS and the conservation tech community I am mostly here for the badges!!
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Msc student in wildlife management and conservation
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Our panel of international experts has been hard at work reviewing the 47 proposals we recieved for innovative technological tools to address human wildlife conflict. The panelists have systematically been assessing the...
20 October 2017
The Domain Awareness System (DAS) is a revolution in monitoring technology, creating real-time awareness of protected areas assets. This technology has the potential to completely change standard monitoring procedures...
26 September 2017
Frustrated by the limitations of the tools that were available for managing large camera trap data sets, Heidi Hendry and Chris Mann set out to develop something that met their needs, and thus, Camelot was born. In...
7 July 2017
Funding
The European Space Agency is calling for Kick-Start ideas to leverage space technology for wildlife protection. Three main topics of interest have been identified: 1) Wildlife monitoring, tracking and inventory, 2)...
5 July 2017
Its been a busy couple of months for the Open Acoustic Devices team. They've just returned back from Belize where they have been trialling the new AudioMoth design for gunshot detection. Find out what they've been up to...
27 June 2017
Article
There is a revolution coming in conservation. Advances in conservation technology are generating more data than ever before on what lives where, who eats who, and what’s disappearing and how fast, but it still requires...
10 May 2017
Researchers have identified 15 emerging risks and opportunities for species and ecosystems around the world in a recent horizon scanning exercise.
31 March 2017
The Conservation Leadership Programme (CLP) is a training and capacity building programme that targets individuals from developing countries who are early in their conservation career and demonstrate leadership...
21 November 2016
FishFace is a new application under development by The Nature Conservancy in partnership with Refind Technologies. Similar to facial recognition software used to identify people, FishFace uses artificial intelligence to...
10 November 2016
More than half of all primate species are endangered, including our closest living relative, the chimpanzee. Could Passive Acoustic Monitoring (PAM) be applied to primates as well as it has been for other taxa? In this...
29 June 2016
Operating the largest tropical forest camera trap network globally, TEAM Network has accumulated over 2.6 million images. How can large datasets coupled with new techniques for data management and analysis provide...
28 April 2016
Camera traps have revolutionised wildlife research and conservation, enabling scientists to collect photographic evidence of rarely seen and often globally endangered species, with low expense, relative ease, and...
20 April 2016
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Description | Activity | Replies | Groups | Updated |
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Great talk! I thoroughly enjoyed it. Some high schoolers have done small AI projects(s) and have interest in the wildlife. What resources would you all suggest to further... |
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AI for Conservation, Camera Traps | 4 years 1 month ago | |
DeepForest docs are here. https://deepforest.readthedocs.io/ Welcome to have a look. My experience is that individual trees cannot be distinguished in satellite... |
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AI for Conservation | 4 years 4 months ago | |
Steph, thank you so much for this, this is wonderful :) Really, really apreciate you sharing this with me :) Diving into all of the wonderful resources from you, thank you so very... |
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AI for Conservation | 4 years 4 months ago | |
A call put out over on Twitter by Jesse Alston might be of interest here - both for conservationists and grad students. Looks like... |
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AI for Conservation | 4 years 4 months ago | |
This can be done, happy to help :) But I think I need to understand the situation a little bit more. Do you already have the data for training / inference? Do you have any... |
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AI for Conservation | 4 years 4 months ago | |
Hi there this post on Conservation X labs recently came up on designing softwarre for individual horse recognition: https://... |
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AI for Conservation | 4 years 5 months ago | |
Wildlife Insights launched their online platform hosting over 4 million camera trap images. They use AI to automatically classify the... |
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AI for Conservation | 4 years 7 months ago | |
Hey everyone! My colleagues and I are hosting a workshop on Animal Re-ID, and the submission deadline is a little less than a month... |
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AI for Conservation | 4 years 8 months ago | |
Chuck's Python for Everyone course is available these days at www.py4e.com, and he's also created a course called Web Apps for Everyone www.wa4e.com. Both... |
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AI for Conservation | 4 years 9 months ago | |
Hi all! This is a great article summarizing new applications for AI for conservation, and highlights @vsahai 's work with... |
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AI for Conservation | 5 years ago | |
Wild Me (wildme.org) is looking to retain a UI/UX Machine Learning Engineer to help translate advanced ML into beautiful interfaces... |
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AI for Conservation | 5 years 1 month ago | |
Wild Me (wildme.org) is looking to hire a second, Masters or PhD-level Senior Computer Vision Engineer to focus on individual ID of... |
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AI for Conservation | 5 years 1 month ago |
Two-year Postdoc (extendable) in AI and Remote Sensing to Monitor Earthworms in the Field
16 July 2024 9:02am
REDAA is hiring a consultant to explore AI - DEADLINE EXTENDED
11 July 2024 12:33pm
ForestSAT
5 July 2024 7:04pm
Question About Interpolation
18 June 2024 10:52pm
Workflow for automated precise seeding with drones and artificial intelligence
20 June 2024 12:22pm
FOSS Geospatial Tools
Deep learning & bioacoustics postdoc in Cape Town, South Africa
14 June 2024 1:52pm
Conservation Technology for Human-Wildlife Conflict in Non-Protected Areas: Advice on Generating Evidence
22 January 2024 11:36pm
4 February 2024 8:16am
Hi Amit,
The most important thing is that the livestock owners contact you as soon as possible after finding the carcass. We commonly do two things if they contact us on the same day or just after the livestock was killed:
- Use CyberTracker (or similar software) on an Android smart phone to record all tracks, bite marks, feeding pattern and any other relevant signs of the reason for the loss with pictures and GPS coordinates. [BTW, Compensation is a big issue -- What do you do if the livestock was stolen? What do you do if a domestic animal killed the livestock? What if it died from disease or natural causes and was scavenged upon by carnivores afterwards?]
- In the case of most cats, they would hide the prey (or just mark it by covering it with grass or branches and urinating in the area). In this case you can put up a camera trap on the carcass to capture the animal when it returns to its kill (Reconyx is good if you can afford it - we use mostly Cuddeback with white flash). This will normally only work if the carcass is fresh (so other predators would not be able to smell it and not know where it is yet), so the camera only has to be up for 3-5 days max.
This is not really high-tech, but can be very useful to not only establish which predator was responsible (or if a predator was responsible), but also to record all the evidence for that.
13 June 2024 8:58pm
Hey Amit,
This is a great question; from our work, we've seen people do a couple of things. We've even seen people using Ring doorbell footage in urban areas as evidence.
The best thing we've seen is matching the community needs with existing infrastructure:
- Are there existing cameras you can leverage, like the doorbell cameras?
- Can public participation monitoring service this, i.e. public submitted photos and videos?
It also totally depends on the wildlife species you're working with, the interaction, damages, etc. If you've found any good solutions, let me know. I'd love to share that information with our clients here who have constant bear problems.
14 June 2024 9:09am
In that case, you might want to keep an eye on the project from @Lars_Holst_Hansen
Bezos Earth Fund, AI for Climate and Nature Grand Challenge call for $50K-2M projects
12 June 2024 2:58pm
Postdoctoral Research Associate: Bioacoustics & population modeling
11 June 2024 9:35pm
Fully funded PhD in AI biodiversity monitoring
11 June 2024 1:07pm
AI Identification Models on Thermal Data
6 June 2024 8:30pm
7 June 2024 4:06am
Wow! This dataset seems great and definitely worth trying out. Do you perhaps have a dataset for deer, elk, and those animals of the sort?
I live in the mountainous region so deer are very common and easily hit.
Thank you again
7 June 2024 5:43pm
Sorry, the only other dataset of thermal camera trap images that I'm aware of is mostly elephants, although it does have some goats:
https://github.com/arribada/human-wildlife-conflict?tab=readme-ov-file#elephant-dataset
7 June 2024 7:28pm
No worries! I'll be trying the other one to see how it works. Thank you for your help!
VIHAR-2024 deadline extension, June 30th (Interspeech satellite event)
5 June 2024 10:30am
5 June 2024 3:05pm
Thanks for sharing this @nkundiushuti ! I think this post would be better suited as an event, that way it will show up on the WILDLABS event calendar page. Let me know if you have any questions on how to make an event post! You just click the +Post button in the top right corner, then click "event."
7 June 2024 8:29am
hi Alex!! I already posted the event, I just wanted to posted an update: the deadline was extended.
7 June 2024 1:45pm
Fantastic!!
€4,000 travel grants for insect monitoring an AI
6 June 2024 4:49pm
Has anyone combined flying drone surveys with AI for counting wild herds?
14 April 2024 3:40pm
27 May 2024 10:55am
Actually my Raspberry Pi application is a sound localizer not related to image recognition. My image recognition related project runs on Jetsons and higher.
But I think recognizing bugs on a drone would likely be challenging. You would have to have sufficient detail to get good recognition which would be a very narrow field of view and then vibration also becomes an issue.
For example, the trainings on just the coco dataset seems to distill the recognition of people to a multi-segmented thing with bits sticking out. So spiders on camera lens are highly likely to be seen as people. To get better results much more training data is needed. I expect it's also likely to be the case for insects, really large amounts of training data would be needed to tell the difference between different types.
31 May 2024 5:47pm
Hi Johnathan,
There is a Canadian company more or less doing that. They have their own endurance drone and optical/thermal cameras. Very much keyed into surveys and they may have success given the number of helicopter accidents we have had in Western Canada. Not sure if the AI part is there yet.
I know they've done surveys with at least one department here but not much beyond that. I talked to one of the developers their just as a point of interest. The current leadership today looks different than I remember though.
6 June 2024 2:48pm
The camera can be aimed at the greenhouse background, which is like a huge green screen. Inside the greenhouse there's only a few flying insects, and they would all have to fly between the optics and the wall or roof eventually. Or if the bot is flying, have it look upwards.
It's pretty much a programing question. Unfortunately I am not the type of person who is good at both building and troubleshooting hardware, and writing code. I took some programming back in college but I am not sure if I want to get myself up to speed. It's starting to sound like I need a few years of college before I can even get started. Which I already did, too bad none of it counts for anything anymore. Or I guess I can compete in the marketplace with people with real money behind them, which is the only thing that means anything. If you are brilliant and not funded, you might as well be a scarecrow.
New WILDLABS Funding & Finance group
5 June 2024 3:24pm
5 June 2024 4:14pm
6 June 2024 1:38am
6 June 2024 4:16am
Apply! 2024 Conservation Tech Award
3 June 2024 3:51pm
Recruiting for a paid study on Explainable AI & bird identification
1 June 2024 8:34pm
Announcing: BeetlePalooza 2024
31 May 2024 9:00pm
🌟 Seeking a Mentor in Software Engineering 🌟
30 May 2024 10:46am
Bioacoustics and AI 101
29 May 2024 2:21pm
9th Workshop On Detection and Classification of Acoustic Scenes and Events
28 May 2024 8:57pm
32nd European Signal Processing Conference
28 May 2024 8:44pm
5th World Ecoacoustics Congress
28 May 2024 8:07pm
Computational Entomology Webinar III: Processing liquid samples
22 May 2024 12:40am
DeepDive: estimating global biodiversity patterns through time using deep learning
20 May 2024 4:51pm
These authors "develop an approach based on stochastic simulations of biodiversity and a deep learning model to infer richness at global or regional scales through time while incorporating spatial, temporal and taxonomic sampling variation."
4th International Workshop onCamera Traps, AI, and Ecology
9 May 2024 1:00pm
Harnessing large language models for coding, teaching and inclusion to empower research in ecology and evolution
9 May 2024 12:51pm
Check out this paper that reviews the current state of AI in conservation.
28 June 2024 6:35pm
The use of synthetic training data such as interpolated sequence values is common, but fraught with the issue of your synthetic signal generating features that are not true to real life.
Instead, you might think about about appending the values of two long-period sin waves per input element to the sequence going in to your first linear / fully-connected layer. The simplest thing that could possibly work would be to interpret minute of the day and day of the month as the values of your sin wave! (Or perhaps minute/hour if all training sequences are quite short.) Since you’re doing sequence prediction, you would add the appropriate values for each image(?) in the sequence being evaluated.
With that additional signal going in to the model in the early layers, the NN should have a good chance of learning that the differences in the modulating signal corresponds to distance in time.
This technigue was popularized by early Large Language Models to encode the distance between words. There’s been refinement (search “Rotary Encoding” for instance) but the basic idea of sin waves generalizes well.