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!
- @mariahmeek
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Michigan State University
Dr. Mariah Meek is the PI and co-founder of iCatch, an Associate Professor at Michigan State University, and the Director of Research at The Wilderness Society.
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- @aranFish
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CTO at SafetyNet Technologies
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- @Alex.S
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MSc Marine Biologist and Data Scientist, Co-Founder and CSO & CTO of Galene Pathways
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PhD candidate studying the ethics of tech in human-animal interactions.
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Chartered Geographer and Fellow of the Royal Geographical Society. 32 years in GIS, currently as a Senior Product Manager. Main interests: biogeography, biodiversity, ecosystem integrity, ecosystem services, rewilding.
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- @nabilla.nuril
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Incoming student of UCL MSc Ecology and Data Science
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- @Hansa
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- @negar_sadr
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User experience designer focusing on marine mammal conservation through UX-driven exploration of bioacoustics.
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- @valeria
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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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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
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20 April 2016
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10 March 2016
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18 February 2016
New horizon scanning report published this month identifies 15 emerging threats and opportunities for global biodiversity.
3 February 2016
From artificial “sniffer” technologies to portable DNA sequencers, the Wildlife Crime Tech Challenge received hundreds of innovative ideas to help stamp out wildlife crime. Now, the Challenge is proud to announce 16...
22 January 2016
Dr. Lucas Joppa, Scientist at Microsoft Research, considers the evolving impact of data in conservation and society. He examines the difference between ‘big data’ and ‘small data’, and explores how models such as the...
22 December 2015
John Amos, President of SkyTruth, explores how remote sensing is being used in conservation today and the importance of sky-truthing. He examines the role that citizen scientists can play in increasing transparency in...
21 December 2015
Gary Atkinson, Director of Emerging Technologies at ARM, explains why we should be interested in the Internet of Things. Could it be a game changer for conservation?
10 December 2015
The 2015 Fuller Symposium brought together thought leaders in science, policy, business, conservation and development to tackle emerging issues facing our planet. This framing piece was developed to support a Fuller...
26 November 2015
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Description | Activity | Replies | Groups | Updated |
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No worries! I'll be trying the other one to see how it works. Thank you for your help! |
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AI for Conservation | 2 minutes 39 seconds ago | |
Fantastic!! |
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Acoustics, AI for Conservation, Biologging, Build Your Own Data Logger Community, Community Base, Early Career, Ethics of Conservation Tech, Marine Conservation, Open Source Solutions | 5 seconds ago | |
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... |
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AI for Conservation | 1 day 16 hours ago | |
Hi David - have you seen this opportunity? It may be a good one to apply to for support (the Darwin Initiative). |
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AI for Conservation, Drones, Emerging Tech, Human-Wildlife Conflict, Wildlife Crime | 3 days 10 hours ago | |
Hi everyone! I’m sending some information for a paid user study about Explainable AI and bird identification that may be of interest:Our... |
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AI for Conservation, Citizen Science | 5 days 16 hours ago | |
I am also commenting for future notifications - very interested to hear some responses.While not directly related to AI, here in Canada there's quite a conversation around data... |
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AI for Conservation | 2 weeks ago | |
Yes, this system is designed to be installed near farms. We also have the repeller system with audio & light, that is battery & solar powered. This system is a "last line... |
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AI for Conservation | 3 weeks 5 days ago | |
Undoubted things will quickly evolve from just "straight" ChatGPTn, BARD, ClaudeAI, etc "standard" models, to more specialized Retrieval Augmentation Generation (RAG) , where... |
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AI for Conservation, Emerging Tech | 1 month ago | |
This is so cool! I am 1000% going to see if they want to come talk about it at Variety Hou! |
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AI for Conservation, Citizen Science | 1 month ago | |
Hi Sol,If the maximum depth is 30m, it would be worth experimenting with HydroMoth in this application especially if the deployment time is short. As Matt says, the air-filed case... |
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Acoustics, AI for Conservation, Data management and processing tools, Emerging Tech, Sustainable Fishing Challenges | 1 month ago | |
Online citizen science platforms like iNaturalist and Macaulay Library contain a wealth of images but are hard to search using text. We are... |
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AI for Conservation, Citizen Science | 1 month ago | |
We're seeking training data for AI for wolf ID - we at T4C manage 3 Wildbook platforms: Wild North, Whiskerbook and the... |
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AI for Conservation | 1 month 1 week ago |
Challenge: ElephantEdge
11 August 2020 12:00am
Event: StreamingScience's #Tech4Wildlife Thursdays
3 August 2020 12:00am
Automated Fish Identification and Abundance Using Artificial Intelligence
28 July 2020 12:00am
BearID To Go
21 July 2020 12:00am
Competition: Cornell Birdcall Identification
8 July 2020 12:00am
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
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.