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!
- @jdomingo
- | He/Him
I am an enthusiast for nature, technology development, biodiversity conservation and nature inspired design. I posses a technical and environmental background, and I am looking to explore the potential that advance technology has to empower the field of nature conservation.
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- 9 Discussions
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- @eccrc25
- | she/they
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- @och3k
- | she/her
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CIBIO-InBio
I am a PhD student working on wolf bioacoustics. I am combining Audiomoths and Deep Learning into more efficient wolf monitoring protocols. My main field of interest is population ecology.
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- @nadyam
- | she/her
Michigan State University
Conservation geneticist at Michigan State University. Co-founder of iCatch. Solving problems in monitoring, traceability, and enforcement through rapid species identification tech.
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- 3 Discussions
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Passionate advocate for nature and experienced communicator, looking to explore opportunities to leverage technology in wildlife and marine conservation
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Technologist and Visual storyteller focusing on social, conservations issues.
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- @nlubcker
- | Dr
Results-Driven R&D Project Manager | Data scientist | I'm a versatile professional with 10 years of global experience in conservation and research.
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- 1 Discussions
- 7 Groups
- @mariahmeek
- | she/her
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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- @Alex.S
- | She/Her
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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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 |
Passive Acoustic Monitoring: Listening Out for New Conservation Opportunities
29 June 2016 12:00am
Wildlife Crime Tech Challenge Accelerator Bootcamp
24 June 2016 12:00am
Digitising powerlines in bird migratory pathways
14 June 2016 8:53pm
Computer Vision to Identify Individual Animals
29 May 2016 4:52am
TEAM Network and Wildlife Insights
28 April 2016 12:00am
Is Google’s Cloud Vision useful for identifying animals from camera-trap photos?
20 April 2016 12:00am
ContentMine: Mining Helpful Facts for Conservation
5 April 2016 12:00am
Disruptive Technology: Embracing the Transformative Impacts of Software on Society
10 March 2016 12:00am
Ecotech Grants from the Captain Planet Foundation
18 February 2016 12:00am
Upcoming GIS and Remote Sensing Courses
9 February 2016 12:00am
[ARCHIVED] Job: ML developer at Skytruth
3 February 2016 1:22pm
Report outlines 2016's most pressing conservation issues
3 February 2016 12:00am
Wildlife Crime Tech Challenge: Winners Announced!
22 January 2016 12:00am
Introductions
10 December 2015 8:13pm
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
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: [email protected].
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
6 June 2016 11:17am
Hi Jason,
Thanks for sharing this demo, it's interesting to see the fluke id process in action. Is this part of the flukebook project? How do you see the project progressing - are there opportunities for people to get involved or challenges it would be helpful to get outside input on?
Cheers,
Stephanie