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!
- @negar_sadr
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User experience designer focusing on marine mammal conservation through UX-driven exploration of bioacoustics.
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Studio Pixel
AI integration architect, AI product manager. I've built the front-end of this website 😁
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Stellenbosch University & The Cape Leopard Trust
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- @LianaN
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- @Harperinos
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'Diploma of Conservation & Ecosystem Management' student at TAFE NSW Australia.
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- @KelseyGrace
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Hello! I am PhD student studying Animal behaviour and welfare at the University of Lincoln. I am specializing in studying gopher tortoise cognition and applying what we learn to conservation practices.
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- @LouisaRC
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LRC Wildlife Conservation
With 20 years' experience as a Conservation Practitioner, I've transitioned from carnivore scientist to Dean, nurturing African conservation leaders. My focus now is on leveraging innovative Web 3.0 technologies for maximum conservation impact.
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Heading up comms for a conservation agency based in the United Arab Emirates
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- @roboticscats
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Founder & CEO of RoboticsCats, a machine vision startup. Our AI wildfire detection SaaS is protecting forests & communities in Asia, Europe & LATAM.
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African Parks
African Parks/D.R. Congo
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Description | Activity | Replies | Groups | Updated |
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You should join the Key Conservation app, which connects people and NGO's for specific needs, whether funding, time, or skills (programming included). Organizations can list... |
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AI for Conservation | 3 years ago | |
Thank you VERY much for that, Carly. I really appreciate it. I have only heard of the bear research project and was not aware of the others. This is very helpful. FYI: Most... |
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AI for Conservation | 3 years 2 months ago | |
The Atlas Coral Atlas combines high-resolution, seamless satellite imagery mosiacs, image processing techniques, machine learning, and... |
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AI for Conservation | 3 years 2 months ago | |
Sure thing, I'll email you directly. |
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AI for Conservation | 3 years 2 months ago | |
Hi Wildlabbers, This week is the last episode of Tech Tutors Season 2! Elizabeth Bondi tackled the question "How do I... |
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AI for Conservation, Drones | 3 years 3 months ago | |
Thanks Carly, These are great ideas. The movebank recommendation reminds me of some work from Save the Elephants that used its transparency to exonerate an elephant that had... |
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AI for Conservation | 3 years 3 months ago | |
This works very well, and can remove the movie strip icons from the edges of the thumbnails, which obscure animals just coming into the frame. https://icaros.en.softonic... |
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AI for Conservation | 3 years 3 months ago | |
Dan's comments about the need for technologists and conservationists to manage and share (properly annotated) data struck a chord with me, it was right at the end of the... |
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AI for Conservation, Data management and processing tools | 3 years 3 months ago | |
Hi Alex, that sounds great! Feel free to email me at [email protected], that may be simpler. |
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AI for Conservation | 3 years 3 months ago | |
Hi. Just watched the Youtube version (I'm in the unable to watch live hemisphere) and wanted to say that was a great talk. I wish it could have gone for another hour. I liked... |
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AI for Conservation, Camera Traps | 3 years 4 months ago | |
I know I'm very late, but I only discovered this recently. Is your team still active/accepting new members? |
+24
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AI for Conservation | 3 years 4 months ago | |
Hi @pmnguyen1224 , thanks for reaching out and checking out the system! We would love to help ensure that you're able to get pattern matching to work for... |
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Acoustics, AI for Conservation | 3 years 5 months ago |
Tech Tutors: How do I get started using ML for my camera traps? Building Accurate Project-Specific Models
25 June 2020 12:02am
26 June 2020 2:32pm
Hi everyone!
We've now posted Sara's session to our youtube channel, and I've also popped it up the top of this thread.
The collaborative notes worked really well! I've now updated them to capture what happened in the chat - it should be a helpful companion to go alongside the recording. The notes have links, projects, and key discussions we saw in the chat, and summarise the questions Sara coverd in the discussion as well as the Qs we weren't able to get to (40mins overtime was our limit!). If your question was one of the outstanding ones and you'd like to have it answered, please drop it in the discussion below.
The notes now also have the participant check ins (such an awesome range of places, projects and interests!) - I'm sharing these as seeing what other people are doing might help you connect with each other. If you see someone you want to connect with, try and find them using our member direcyour people tab. If you can't, email Ellie and she will see if that person is happy to hear from you before connecting you.
Reminder, registration is open for Carlos' tutorial next week: How do I perform automated recordings of bird assemblages? Register here.
Thanks everyone!
Steph
2 July 2020 8:58pm
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 develop high schooler’s interest in AI?
How do I scale up acoustic surveys with Audiomoths?
25 June 2020 12:00am
How do I perform automated recordings of bird assemblages?
19 June 2020 12:00am
How do I train my first machine learning model?
9 June 2020 12:00am
How do I get started using Machine Learning for my camera traps?
9 June 2020 12:00am
Innovator Interview: Hack the Poacher
4 June 2020 12:00am
The Perfect Paw Print: Collecting Data with FIT
3 June 2020 12:00am
Competition: 2020 Hackaday Prize
26 May 2020 12:00am
WILDLABS Tech Tutors: Season One
19 May 2020 12:00am
Get To Know FIT
6 May 2020 12:00am
Competition: iWildCam 2020
4 May 2020 12:00am
Training Course: Quantitative Analysis of Marine & Coastal Drone Data
29 April 2020 12:00am
Call for Submissions – Arm Research Summit 2020
24 April 2020 12:00am
WILDLABS Tech Hub: WWF PandaSat
13 April 2020 12:00am
Webinar 11PST 3/20 - Deep Learning for Airborne Tree Detection
17 March 2020 1:28am
17 March 2020 3:52pm
Thanks Ben. I'll see what I can do.
24 March 2020 9:57am
Hello Ben. Unfortunately I couldn't make it on Friday. It would be great if I could take a look at your slides. I'm interested in trying to count mangrove trees. I have some WorldView 2 data. Do you think I could use DeepForest for this?
31 March 2020 4:21am
DeepForest docs are here.
https://deepforest.readthedocs.io/
Welcome to have a look. My experience is that individual trees cannot be distinguished in satellite imagery. The coarest resolution we've had success with is 0.3m. However, the deepforest weights may still useful as a starting location. If there are visible objects in your image that you want to detect, collecting a few hundred training data samples and retraining the model for 2-3 epochs could be useful. See the link for details. Happy to help, submit issues on the github repo is something isn't clear/doesn't work. Everything is in dev.
WILDLABS Community Call Recording: Rainforest X-PRIZE
30 March 2020 12:00am
Open, challenging dataset for audio classification
27 March 2020 10:52am
27 March 2020 11:51am
Hi Radek,
I'm sure others can help here, but check out our recent virtual meetup (it'll be posted here in about an hour), the speakers - particularly Dave Watson - shared open datasets that might be what you're looking for.
Over on Twitter, Jesse Alston is collating a google sheet so that people can advertise data sets that grad students can use to finish theses. @arik 's reply here might be of particular interest: 'We have been recording 24/7 soundscapes in remote US locations like Yellowstone NP and rural central Wisconsin with multiple GPS synced recorders. Our goal is to study wolf and coyote vocalisations, but if anyone can make use of these data for their own studies, drop me a line!.'
Hope this helps!
Steph
27 March 2020 12:25pm
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 much for this!
Radek
Help collate list of Ecology/Conservation Data Sets for grad students
27 March 2020 12:07pm
Automated species detection from camera traps
30 January 2020 8:43am
25 March 2020 2:59pm
I see. Im interested and would like to help. I will need the images to train the network. As many as possible.
if you dont have them yet, try to find similar images preferably of the same species. I will use them to test the performance of the detection.
25 March 2020 6:49pm
I'm not familiar with camera traps, but there are a couple of options:
1) If the animals tend to cover most part of the image, then you can train a CNN classifier to distinguish between species (available with the keras-Tensorflow modules in Python)
2) If, however, the animals only cover a small part of the image (e.g. in the distance), it might be better to use an object detector (I've used YOLOv2 in the past for fish detection), which however is not that straightforward, especially with Python (I used MATLAB)
In any case, keras-Tensorflow classification with Python might be the most straightforward option for your goal. You should also certainly have a look at Google's Wildlife Insights platform which is specialized for species classification from camera trap images.
27 March 2020 10:33am
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 example images with the species in them annotated? Say a still from the camera with a tiger and a csv file referencing that file and annotating that there is a tiger in the image?
Would you like someone to do the developing and training of the deep learning model for you? I work as an AI research engineer at the Earth Species project and I am also a part of a community of deep learning practitioners where we apply cutting edge research to various problems. Here you can check a little initiative I started a couple of days ago to teach people how to work with audio (there is a related forum thread but unfortunately it is in closed forums for the time being as it is associated with a course that is under way). My main point is this - if you have the data and would like someone to help you out on the modelling part, I can coordinate this.
Alternatively, if you cannot release the data, I can point you to materials that can get you started to carry out the work yourself.
Webinar: Citizen Science Online
26 March 2020 12:00am
WILDLABS Tech Hub: Poreprint
26 March 2020 12:00am
Enter the Zooniverse: Try Citizen Science for Yourself!
18 March 2020 12:00am
Tutorial: Train a TinyML Model That Can Recognize Sounds Using Only 23 kB of RAM
16 March 2020 12:00am
Accepting Applications: ArcGIS Solutions for Protected Area Management
4 March 2020 12:00am
Competition: Plastic Data Challenge
3 March 2020 12:00am
Call for Nominations: Tusk Conservation Awards
3 March 2020 12:00am
Hawai'i Conservation Conference
28 February 2020 12:00am
Competition: The Artisanal Mining Grand Challenge
26 February 2020 12:00am
Listening to Nature: The Emerging Field of Bioacoustics
24 February 2020 12:00am
Team for Building of ML app for horse identification and conservation
20 February 2020 11:09pm
25 June 2020 6:01pm
This is a big, important question! I think having traceable DOIs for both datasets and machine learning models is a step in the right direction. GBIF is committed to this and can provide data DOIs, read more detail here and here.