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.
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!
CAIMAN is a product from the Sensing Clues Foundation that automatically classifies animals on images from camera traps. It aims to be available by the end of 2021, contact the Sensing Clues team for more details. This...
18 November 2021
The GEO-Microsoft Planetary Computer Programme invites the GEO community to be among the early adopters of Microsoft's Planetary Computer. The Programme will support a number of 12-month projects that use The Planetary...
4 November 2021
On 3rd November 2021, Earthranger Announced Giraffe Conservation Foundation and Lion Guardians as the inaugral Conservation Tech Award Recipients. The two organizations are Harnessing the Power of Technology to Protect...
3 November 2021
The Centre for Statistics in Ecology, Environment and Conservation, a research group within the Department of Statistical Sciences at the University of Cape Town, is now hiring for a funded postdoc or PhD postion with...
1 November 2021
This article explores the use of IoT and Machine Learning Technologies in Ewaso Nyiro River, Kenya - which serves several communities as well as wildlife in Olpejeta Conservancy and Lewa Conservancy, among others. Data...
21 October 2021
The International Journal of Computer Vision is calling for papers on Computer Vision Approach for Animal Tracking and Modeling. Visit the Springer website for further details and submission guidelines.
20 September 2021
In this thought piece from Whale Seeker, Malcolm Kennedy considers the strengths of weaknesses of citizen science and AI, both used to analyze large amounts of conservation data, and discusses the importance of data...
19 August 2021
Today, we're chatting with our WILDLABS Fellowship: On the Edge partners at Edge Impulse about how conservation tech funding and support can be more sustainable, and why reimagining how fellowships make an impact is so...
13 August 2021
To celebrate our newly-lauched WILDLABS Fellowship: On the Edge, I spoke with the Edge Impulse team about why uniting the conservation and tech worlds to make funding, tools, training, and support accessible and...
9 August 2021
Wildlife Insights is excited to announce the public release of their new platform! Read on to learn about all the useful features you'll find on Wildlife Insights, and check out WILDLABS' Tech Tutors episode with...
27 July 2021
Our friends at BearID joined an EXPLORE.org live chat to discuss their work identifying the bears of Katmai National Park with powerful AI technology. Watch the full panel event below, or here on EXPLORE.org's Youtube...
1 July 2021
A new issue of Methods in Ecology and Evolution from the British Ecological Society is now available for download. In this issue, WILDLABS readers will enjoy research involving conservation dogs and non-invasive...
23 April 2021
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New article: Domain-specific neural networks improve automated bird sound recognition already with small amount of local data
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Hierarchical Deep Learning to Improve Automatic Classification of Pests and Biodiversity Monitoring in Agroecosystems
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New paper: Integrating machine learning, remote sensing and citizen science to create an early warning system for biodiversity
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Opinion paper describing "how data acquired from remote sensing, citizen science & other monitoring approaches could feed in near-real time to an early warning system for biodiversity that integrates automated red-listing of species with the identification of priority areas for conservation."
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