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!
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Hi Tyler,
Would like to introduce you to Ceres Tags products
- Ceres Tags products come in boxes of 5, 10 and 24.
- There are some software partners such as Earthranger, Mapipedia and possibly CiboLabs that would be able to assist you with your mapping vegetation requirements
- Ceres Tag does not require any towers, base stations and infrastructure. This allows you to see any movements from the heard outside of their normal herd (boundary alerts), and you will not be disturbing any of the flora and fauna with infrastructure set up.
- For the timing you are looking at, Ceres Wild pings directly to satellite 24 times a day. For Ceres Trace and Ceres Ranch there are 4 within 24 hours. Taking into consideration, when you set up alert areas, you will get them directly to your phone/laptop via your software of choice
- Ceres Ranch is a reusable tag that has just been launched. Use it on this project, remove the tag and then use the tag on your next project
- The software you choose will assist with the history of your animal movements. Ceres Tag is integrated with 11 software partners and in-development with 18 software partners https://cerestag.com/pages/software-partners
- Understanding it is a short-term project, you would be able to use Ceres Tags products without the additional expense of setting up and removing infrastructure- towers, gateways
- With Ceres Tag, you are purchasing the box of tags and picking a suitable software to deliver the information you require. On average, a box of 10 Ceres Trace Tags, is the same as 1 LoRaWAN tower.
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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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Hey Sara,
Thanks again for the session today--it was super helpful!
I have access to a pretty large network of camera trappers, and I'm currently surveying them to see who might be willing to share data with me. That being said, I can likely get data-sharing agreements with each of these agencies sorted out before the application deadline, but may not have the data in-hand by this time due to a lack of resources for transferring such large amounts of data.
I've used Azure Storage Explorer before to rapidly transfer large datasets like this, so I think it might be easier to compile all data in one location once we have access to the VMs. Would it be acceptable to apply with the signed data-sharing agreements in mind, and with the intent of organizing all of the data once we acquire access to the computing resources?
4 November 2022 6:02pm
Yes, that's definitely ok! You should just outline your larger plan and where you are at in the process in your application. However, the compute resources are intended to be used for model training and won't be available too far in advance of the school (or at least I can't guarantee they will be) , so you would need to make a plan for pre-summer workshop data storage, wrangling, and curation to get the data ready to train models on. Let me know if you're having issues with that and I can try to help brainstorm.
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More info:
Feel free to comment here or message me directly if you have any questions!
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Maybe she is not based in Asia, but you could check Lily Xu, who gave a presentation at the IUCN World Congress a year ago on using AI against poaching in Cambodia. The project is called Protection Assistant for Wildlife Security (PAWS).
For a summary of this project and another ( presented by a man ) see
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Thank you so much!
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Hahaha, now I see why you were asking ...
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Out of curiosity, what are the similarities/differences between your platform and other image classification ones such as Wildlife Insights, WildID, ZambaCloud? I don't mean that in like a "what's best" way, just would be great to better understand the the details so that people can assess what to try for their specific use cases & applications!
It would be great to have a comparative specs sheet of sorts! Peter Gyurov started something like that: https://www.notion.so/Camera-Trap-Pipeline-Solution-Comparison-2eac80825c4941b0b2b5fad3daea1cc3. Would be great to add ConservationAI to this list!
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Why would you want to avoid alerting the rangers ?
You don't need high tech for this; elephants leave very obvious tracks and sign.