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!
I am a AI researcher passionate about wildlife conservation.
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PhD student using Geo-AI and remote sensing to address environmental problems
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Founder of Wildya & Wild Business Mates / With Wildya - I combine nature & personal development / With Wild Business Mates - I help biodiversity heroes like you to get better at business
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- @eliminatha
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Passionate wildlife researcher dedicated to uncovering the secrets of the natural world via the lens of camera traps. With a sharp eye for detail and a strong commitment to wildlife conservation.
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- @Amitkaushik
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University of Georgia (UGA)
Environmental anthropologist; An interdisciplinary Ph.D. student, bridging conservation science, policies, and social justice
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Data has been my passion and i enjoy working with data while bringing value to the business. Data engineer with 7+ years of experience Eager to support with expert analytical skills to advance the companys business operations and strategic initiative.
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- @kbubnicki
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Ecologist, data scientist, and programmer with over 13 years of professional experience. Open source and Linux enthusiast. Researcher at the Mammal Research Institute, Polish Academy of Sciences, and CEO of the Open Science Conservation Fund.
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- @JoãoVieira
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Conservation biologist. Iberian wolf monitoring field technician. Master`s on bear`s movement ecology.
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- @shannondubay
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Panthera
Director of Conservation Technology at Panthera
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- @waltertortuga
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Universidad San Francisco de Quito
I'm a professor and researcher focusing on carnivore conservation in tropical landscapes.
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- @silvanasitayiari
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Article
Article from Ars Technica about how difficult it is to detect and avoid kangaroos...
3 April 2024
18 month postdoc research position, Netherlands, EU-funded
28 March 2024
Article
You’re invited to the WILDLABS Variety Hour, a monthly event that connects you to conservation tech's most exciting projects, research, and ideas. We can't wait to bring you a whole new season of speakers and...
22 March 2024
Join our multi-national team at the AI for Biodiversity Change Global Climate Center! We're hiring a Research Data Manager & Tech Coordinator at Ohio State. Support cutting-edge research on climate change &...
15 March 2024
Catch up on the conservation tech discussions and events that happened during World Wildlife Day 2024!
7 March 2024
EcoAssist introduces a free African species identification model for camera trap images, capable of recognising 30 species.
5 March 2024
Join us to help prevent biodiversity loss! Understory is hiring a postdoc to lead R&D Development on generalizing Computer Vision models for vegetation identification across space/time/phenotypes.
29 February 2024
Join the Luxembourg Institute of Science and Technology (LIST) in pioneering environmental and ecological monitoring! 🌍💡 As part of ERIN’s Observatory for Climate, Environment, and Biodiversity (OCEB), you'll be at the...
26 February 2024
SNTech are recruiting for 3 roles to assist us to develop computer vision pipelines for underwater monitoring
15 February 2024
We invite applications for the third Computer Vision for Ecology (CV4E) workshop, a three-week hands-on intensive course in CV targeted at graduate students, postdocs, early faculty, and junior researchers in Ecology...
12 February 2024
The primary focus of the research is to explore how red deer movements, space use, habitat selection and foraging behaviour change during the wolf recolonization process.
10 February 2024
Applications open for a PhD position in plant vibroacoustics at the University of Southampton
8 February 2024
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Description | Activity | Replies | Groups | Updated |
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Yes please reach out with any questions on acoustic monitoring, Arbimon, RFCx, etc.! |
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Acoustics, AI for Conservation, Data management and processing tools | 1 year 2 months ago | |
I couldn't agree more with both of these comments tom! I'm reading hundreds (literally hundreds) of applications for open WILDLABS roles at the moment, and the ones that stand out... |
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AI for Conservation, Drones, Early Career, Sensors | 1 year 2 months ago | |
We have made available our underwater videos on YouTube as a playlist https://www.youtube.com/playlist?list=PLnhVZKKy8WkZKriCIV6r7upWhHNVrU_7L It's about 1.113 short video... |
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AI for Conservation, Camera Traps, Data management and processing tools, Marine Conservation | 1 year 3 months ago | |
Hi Steph, This should be a simple project. Recently I came across a website with a sample video I am not sure whether it was from the wild Labs website. Where a camera is... |
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AI for Conservation, Camera Traps | 1 year 3 months ago | |
Bluesky have a commercial tree crown dataset available covering most of Great Britain (England, Wales and parts of Scotland). There is a canopy layer with approximate outlines of... |
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AI for Conservation, Drones | 1 year 3 months ago | |
Rainforest Connection's (RFCx) Guardian devices may be of interest. They are solar-powered and have connectivity options for Wifi, GSM and satellite transfer. They've previously... |
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Acoustics, AI for Conservation, Connectivity, Data management and processing tools, Protected Area Management Tools, Sensors | 1 year 3 months ago | |
My original background is in ecology and conservation, and am now in the elected leadership of the Gathering for Open Science Hardware which convenes researchers developing open... |
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AI for Conservation, Biologging, Camera Traps, Conservation Tech Training and Education, Data management and processing tools, Drones, Emerging Tech, Sensors | 1 year 4 months ago | |
Hi Sophie, Can you please help me or get in touch in developing a system where we are able to detect an Elephant? Would like to discuss more about it. Kindly treat this as urgent!! |
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AI for Conservation | 1 year 4 months ago | |
Hello All - @sarabeery et Al have just put a pre-print out on their educational insights into teaching Computer Vision to ecologists. I... |
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Acoustics, AI for Conservation, Conservation Tech Training and Education, Early Career, Emerging Tech | 1 year 4 months ago | |
The Conservation Technology Lab at San Diego Zoo seeks undergrads for summer projects in computer vision, machine learning, bioacoustics,... |
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Acoustics, AI for Conservation, Conservation Tech Training and Education | 1 year 5 months ago | |
I just came across this interesting paper in which seismic monotoring of animals like elephants was mentioned. This is the study refered to:Cheers,Lars |
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AI for Conservation, Camera Traps, Emerging Tech, Ethics of Conservation Tech, Human-Wildlife Conflict, Remote Sensing & GIS, Sensors | 1 year 5 months ago | |
Quick reminder that the deadline for applications is just shy of a week away. This workshop is particularly geared to teach ecologists computer vision tools to apply to their... |
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Conservation Tech Training and Education, AI for Conservation | 1 year 5 months ago |
HWC Tech Challenge Update: Meet the Judges
20 October 2017 12:00am
[ARCHIVED] Fish identification computer vision competition
26 September 2017 8:43pm
DAS: A Scaleable Solution For Protected Area Management
26 September 2017 12:00am
The Greenhouse 2017: Planet Saving Technology Series (Syd, Australia)
19 September 2017 2:01pm
19 September 2017 2:37pm
If you're interested, you can check out the live recordings from past events (links below take you to the videos):
August: The Blockchain
The Blockchain's potential ability to help leapfrog or change corrupt and inefficient power structures can revolutionize the way we approach issues ranging from the supply chain, financial inclusion, human rights abuses, and modern slavery to environmental, energy, and workforce problems.
One source of shared truth and trusted infrastructure can help NGOs, charities, social entrepreneurs, civil societies and companies achieve their mission.
Come and discover the innovators, leaders, and philosophers in the space showcasing their solutions and meet the technologists who can support your needs.
So what is Blockchain, and is it just hype or is it really a Planet Saving Technology?
Speakers and Panellists
• Dr Jane Thomason - CEO Abt Australia, Social Policy Adviser, Devex Impact Strategic Advisory Council, Commentator Blockchain
• Arthur Falls - Director of Media at Consensys / Podcaster, State Change & The Ether Review Podcasts
• Bubba Cook - Pacific Tuna Programme Manager, WWF NZ / Pacific
• Leah Callon-Butler - Member, Advisory Board, RedGrid
• Bridie Ohlsson - External Relations, AgriDigital
July: Virtual Reality and Augmented Reality
With it's origins in science fiction, the idea of Virtual Reality has been around since the 1950's, but in the last few years, with the promise of mobile computing, it's suddenly the talk of the town.
Many are excited by the deep immersive nature and empathetic story telling potential of VR/AR and see huge opportunity in awareness raising and shifting public opinion around important issues.
So what is VR, and it's related technology cousin Augmented Reality, an is it a potential Planet Saving Technology?
Speakers and Panellists
We have a bumper, star-studded panel to unpack, explain and explore this promising technology..
• Kim McKay - CEO, Australian Museum
• Brennan Hatton - Founder, Equal Reality (Augmented Reality Development)
• Parrys Raines - FBGen / Future Business Council / Climate Girl
• Jennifer Wilson - Creative/Digital Strategist, Founder, Lean Forward
• Mikaela Jade - CEO, Indigital (Indigenous storytelling with AR)
• Scott O'Brien - CEO, Humense (Volumetric Video + Virtual Reality) (Panel Moderator)
June: Smart Cities and the Internet of Things
What is a Smart City? How will Smart Cities change the way we organise our lives? Will they bring about the so-called ‘fourth industrial revolution’?
What is the Internet of Things, and does it have the potential to be a Positive Impact Techonology? What are the opportunities and what are the risks?
We explore all this and more in the first of our deep dives into Planet Saving Technology: Smart Cities and the Internet of Things.
Speakers and Panellists
• Frank Zeichner - CEO, IoT Alliance Australia
• Angela Bee Chan - Schneider Electric / Hackathons Australia
• Ben Moir - Snepo Fablab / WearableX
• Monica Richter - Low Carbon Futures, WWF Australia.
• Andrew Tovey - Total Environment Centre, TULIP/Smart Locale (Panel Host)
Deep Learning Project Repository
10 December 2015 7:53pm
5 August 2016 2:38pm
NOAA Right Whale Recognition Competition, January 2016
364 teams | $10,000 prize
https://www.kaggle.com/c/noaa-right-whale-recognition
Competition Details:
With fewer than 500 North Atlantic right whales left in the world's oceans, knowing the health and status of each whale is integral to the efforts of researchers working to protect the species from extinction.
Currently, only a handful of very experienced researchers can identify individual whales on sight while out on the water. For the majority of researchers, identifying individual whales takes time, making it difficult to effectively target whales for biological samples, acoustic recordings, and necessary health assessments.
To track and monitor the population, right whales are photographed during aerial surveys and then manually matched to an online photo-identification catalog. Customized software has been developed to aid in this process (DIGITS), but this still relies on a manual inspection of the potential comparisons, and there is a lag time for those images to be incorporated into the database. The current identification process is extremely time consuming and requires special training. This constrains marine biologists, who work under tight deadlines with limited budgets.
This competition challenges you to automate the right whale recognition process using a dataset of aerial photographs of individual whales. Automating the identification of right whales would allow researchers to better focus on their conservation efforts. Recognizing a whale in real-time would also give researchers on the water access to potentially life-saving historical health and entanglement records as they struggle to free a whale that has been accidentally caught up in fishing gear.
From what I can gather, the winning solution was submitted by deepsense.io. They've written a full blog post about it here:
http://deepsense.io/deep-learning-right-whale-recognition-kaggle/
9 October 2016 12:12am
Wildbook / IBEIS. Open-source effort to combine web-based mark-recapture database with ML/CV photo detection and identification. http://wildbook.org
[ Full disclosure: I am a member of the non-profit team working on this project! ]
2 September 2017 7:40am
Hypraptive and Brown Bear Research Network collaboration to develop a deep learning, brown bear face identification system: BearID Project.
[Disclosure: I am a member of hypraptive, and maintain the hypraptive blog]
MIT's SLOOP: machine learning (ML) animal image recognition
27 July 2017 2:04am
27 August 2017 7:20am
It looks like they haven't updated for a couple of years do you know if it is still active or are they changing to a different system like tensor flow?
From the Field: Developing a new camera trap data management tool
7 July 2017 12:00am
Leverage Space Technology for Wildlife Protection with the European Space Agency Kick-start Grant
5 July 2017 12:00am
Trialing Audiomoth to detect the hidden threats under the canopies of Belize
27 June 2017 12:00am
Pairing Scientists and Citizen Scientists with AI Assistants
18 May 2017 7:06pm
Machine learning, meet the ocean
10 May 2017 12:00am
Acoustics for Human-Wildlife Conflict Prevention, Anti-poaching, and more
27 April 2017 6:35pm
Welch Labs - Learning to see
31 March 2017 11:10am
31 March 2017 11:45am
Ah! Thanks for posting this Tom. It's such a well designed, simple to understand video series, and the backing track is utterly delightful.
Given the growing applications of machine learning for conservation, I've been wondering if a 'machine learning 101 for conservation' webinar or article might be a worthwhile resource to look into for our community. In looking for a link to put in here to a UCL course I know exists on this topic, I actually just came across this article: A PRACTICAL GUIDE TO MACHINE LEARNING IN ECOLOGY. Seems that Jon Lefcheck had the same thought as me and got right down to it.
If you're interested in more introductory, practical resources on machine learning, do let me know below! Also, if you know of any other go to tutorials that you've found useful, please share them.
Steph
15 Risks and Opportunities for Global Conservation
31 March 2017 12:00am
Conservation Leadership Programme 2017 Award
21 November 2016 12:00am
We Can Have Oceans Teeming with Fish with FishFace Technology
10 November 2016 12:00am
Tracking megafauna with satellite imagery
11 October 2016 5:08pm
Zoohackathon: 'END LOOP - Coding to end wildlife trafficking'
22 September 2016 12:00am
Video: Discover the SMART Approach
20 July 2016 12:00am
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
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
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
29 September 2017 1:00pm
Hi Kate,
It's really exciting to hear that you've now launched the challenge, congratulations on getting to this point! It's going to be interesting to see what solutions come out of the challenge - please do keep us updated as it progresses if you have time. The challenge is focused on the New England fishery - are you envisaging that this is an approach you can take to scale and eventually extend to other fisheries?
To add a bit more information for anyone interested, there's actually $50,000 of prizes attached to this challenge:
Place Prize Amount 1st $20,000 2nd $15,000 3rd $10,000 4th $3,000There is also a wildcard prize:
We're also looking for innovative approaches to solving this fishy problem, even if they don't score in our Top 4. If you want to be eligible for our $2,000 Judges' Choice Award, submit your code on the Submit Report page (available once you've signed up) by the competition end date for review. Our judges will be looking for inventive, novel solutions that can be incorporated into video review programs, so share your most fin-tastic ideas.
Finally, if you're curious to find out more about what led to the challenge, Kate actually wrote a piece called 'Machine learning, meet the ocean' that we published in the resources area a few months ago. Do have a read!
Cheers,
Steph