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!
The Department of Wildlife, Fish, and Environmental Studies (WFE), SLU, Umeå, is looking for a postdoc with strong interests in wildlife conservation technology.
26 August 2022
An update on Ceres Tags products that are being used in conservation
22 August 2022
Job opening at ARISE, an innovative program in the Netherlands to build a digital infrastructure for biodiversity data and services
19 August 2022
Bird Sounds Global (BSG) launched a web portal for annotating bird sounds. Annotating means identifying the species vocalising in the recording. The aim is to produce training and testing material for automated bird...
17 August 2022
Are you creative, love new challenges and have experience developing software? The Wildlife Insights team is hiring! Join a diverse team of ecologists, data scientists, engineers and machine learning experts to protect...
10 August 2022
The Marine Robotics and Remote Sensing (MaRRS) Lab at Duke University seeks a highly motivated UAS pilot and geospatial analyst to support the ongoing development of new and existing research and conservation programs,...
10 August 2022
The Marine Robotics and Remote Sensing (MaRRS) Lab at Duke University seeks a highly motivated postdoctoral researcher to support the ongoing development of new and existing research and conservation programs, both...
10 August 2022
Press Release for International Tiger Day – July 29th, 2022: For the first time ever, wild tigers and their prey have been detected by AI-powered, cryptic cameras that transmit the images to the cell phones and...
5 August 2022
A gentle introduction to the exciting field of embedded machine learning.
5 August 2022
We're looking to grow our engineering and ML teams.
3 August 2022
Ceres Tag sends just in time alerts and GPS location to have the power to track and trace.
22 July 2022
The Earth Species Project (ESP) is a nonprofit organization dedicated to decoding animal communication and translating non-human language.
15 July 2022
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15 November 2022 4:08pm
New article: Domain-specific neural networks improve automated bird sound recognition already with small amount of local data
15 November 2022 11:03am
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Hierarchical Deep Learning to Improve Automatic Classification of Pests and Biodiversity Monitoring in Agroecosystems
8 November 2022 3:46pm
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New paper: Integrating machine learning, remote sensing and citizen science to create an early warning system for biodiversity
7 November 2022 7:10pm
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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