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!
Botswana Predator Conservation Trust
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Quantitative ecologist @ Biotope
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Savanna Ecologist, Field Station Director and Head of Conservation Tech Projects for Organization for Tropical Studies (OTS).
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Ecologist & Conservationist. Women for the Environment, Africa Fellow. National Geographic Explorer.
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Nature lover from MA
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Latin American environmental scientist.
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PhD student at UC Davis studying gorilla communication & movement
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Project planet is working to mitigate conflict between farmers and forest elephants in Gabon, Central Africa.
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Wild Me
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I am a AI researcher passionate about wildlife conservation.
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In this interview with Edge Impulse’s Daniel Situnayake, we discuss how we can achieve that balance for machine learning tools, and how to maximize technology’s potential for good.
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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 2 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 | 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 |
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24 February 2019 1:28am
Hi Claire,
At the BearID Project, we are working on a similar problem for brown bears. We are currently using machine learning methods developed for human facial recognition (like Google FaceNet). We got some ok initial results, but now we are running up against small data issues. The method for human faces were trained with millions of images of hundreds of thousandes on individuals. We have a few thousand images of about a hundred individuals. We plan to investigate other methods in the future.
It will be great to keep in touch to see what methods you will be using.
Ed
24 February 2019 1:38am
Hi Colin,
At the BearID Project, we are working on a similar problem for brown bears. We are currently using machine learning methods developed for human facial recognition (like Google FaceNet). We got some ok initial results, but now we are running up against small data issues. The method for human faces were trained with millions of images of hundreds of thousandes on individuals. We have a few thousand images of about a hundred individuals. We plan to investigate other methods in the future.
The last time I talked to WildMe, the identification algorithms were based on matching unique patterns. We didn't think this would be directly applicable for brown bears as they don't have a lot of clearly identifiable markings. Have you developed other identification algorithms?
Ed
Responsible AI for Conservation?
11 February 2019 6:22pm
21 February 2019 8:17am
Hi Jaishanker
Absolutely - the overlap between image-based and sound-based analyses is increasing, and consistent terminology will no doubt help us share info.
Are you using ML in SODA for automated identification of sounds? If so, how are you determining if a given classifier is performing well?
Thanks
Ollie
21 February 2019 11:08am
Hello Ollie,
SODA is a recently launched suite. It is in the development phase. We have with us call libraries with multiple (40+) calls for 10- 12 species of birds. A research scholar is on the job for classifying at the species level.
Our interest is equally on separating the different sonic components (as stated in https://www.wildlabs.net/community/thread/666). It is different from the link shared in my previous reply. This is where I see the confluence of objectives.
As a TEAM, I believe, we can address the individual objectives faster.
regards
jaishanker
21 February 2019 9:13pm
Hi Ollie,
Great article, thank you! I mostly work with responsible AI in other contexts, at Doteveryone.org.uk and the Trust & Technology Initiative at the University of Cambridge, so don't have much to offer here, although I am very interested in the topic. I appreciate your point that many of the consumer data issues highlighted in the 'popular' responsible AI discourse aren't relevant to conservation (some of us have been gathering 'responsible tech' / 'ethical tech' resources in a shared doc, and there's essentially nothing there for conservation specifically - https://docs.google.com/document/d/1SN6hYeKe3eRK6x9D0Sr7GpCA4nirpyo3u68xG1A6NDs/edit ). However there might be some links with humanitarian data practices, which are touched on by the Responsible Data folks at https://responsibledata.io and https://www.fabriders.net/data-literacy-consortium/ or in this recent article https://asecondmouse.wordpress.com/2019/02/20/instability-forecasting-models-seven-ethical-considerations/
Best,
Laura
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30 October 2017 11:46am
Hey Steffen,
I know you've had a student working on this challenge for the past year - how is this project progressing? If you (or your student) have a moment, it would be great to hear an update.
@mmckown shared an in depth write up of one their projects that I thought might be relevant, as it seemed they were tackling something similar to what you are looking into? His team at Conservation Metrics (which presumably included @kleinsound) partnered with Microsoft to automate counts of Red-legged Kittiwakes with ML. I know it's not the exactly the same problem you're looking into, however the post covers their end-to-end flow for object detection, so might have some useful ideas/approaches that may have relevance for your work.
Bird Detection with Azure ML Workbench
Introduction
Estimation of population trends, detection of rare species, and impact assessments are important tasks for biologists. Recently, our team had the pleasure of working with Conservation Metrics, a services provider for automated wildlife monitoring, on a project to identify red-legged kittiwakes in photos from game cameras. Our work included labeling data, model training on the Azure Machine Learning Workbench platform using Microsoft Cognitive Toolkit (CNTK) and Tensorflow, and deploying a prediction web service.
In this code story, we’ll discuss different aspects of our solution, including:
- Data used in the project and how we labeled it
- Object detection and Azure ML Workbench
- Training the Birds Detection Model with CNTK and Tensorflow
- Deployment of web services
- Demo app setup
Steph
23 January 2019 10:12pm
Hello Claire,
Engineer at Wild Me here. We would love to start a conversation about a Wildbook for rhinos.
Lets talk about citizen science and computer vision for identification possibilities. I'm curious about your current data set and the identification tools you are using as a starting point. I'm happy to talk here, or you can email our team at [email protected].