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!
Heading up comms for a conservation agency based in the United Arab Emirates
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Founder & CEO of RoboticsCats, a machine vision startup. Our AI wildfire detection SaaS is protecting forests & communities in Asia, Europe & LATAM.
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African Parks
African Parks/D.R. Congo
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18+ Years of IT experience and worked on all phases of SDLC. Technical reviewer for couple of international books. Looking to break into AI space and want to gain more experience on AI/machine learning
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Purdue University
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Love animals and nature
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Neuroscientist & engineer transitioning to conservation tech. I have experience working with large imaging datasets, pose estimation and positional tracking, and machine learning. Looking to get involved with GIS, remote sensing, and AI for conservation.
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PhD in Ecology, Nature's sound lover.
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Description | Activity | Replies | Groups | Updated |
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There is a South African company Avior labs that successfully does drone surveys on game farms using AI to count and identify wildlife. The trick is to use both infra-red and... |
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AI for Conservation | 22 minutes 52 seconds ago | |
Thank you so much for your support. I am finding it really difficult to find the funding for the initial development. We need lots of engineering time to refine our detection and... |
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AI for Conservation, Drones, Emerging Tech, Human-Wildlife Conflict, Wildlife Crime | 1 day 3 hours ago | |
Yes, this system is designed to be installed near farms. We also have the repeller system with audio & light, that is battery & solar powered. This system is a "last line... |
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AI for Conservation | 1 week 1 day ago | |
Yes, exactly! Alec and I are working together on this. |
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AI for Conservation | 1 week 5 days ago | |
Undoubted things will quickly evolve from just "straight" ChatGPTn, BARD, ClaudeAI, etc "standard" models, to more specialized Retrieval Augmentation Generation (RAG) , where... |
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AI for Conservation, Emerging Tech | 2 weeks 2 days ago | |
This is so cool! I am 1000% going to see if they want to come talk about it at Variety Hou! |
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AI for Conservation, Citizen Science | 2 weeks 3 days ago | |
Hi Sol,If the maximum depth is 30m, it would be worth experimenting with HydroMoth in this application especially if the deployment time is short. As Matt says, the air-filed case... |
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Acoustics, AI for Conservation, Data management and processing tools, Emerging Tech, Sustainable Fishing Challenges | 2 weeks 3 days ago | |
Online citizen science platforms like iNaturalist and Macaulay Library contain a wealth of images but are hard to search using text. We are... |
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AI for Conservation, Citizen Science | 2 weeks 5 days ago | |
We're seeking training data for AI for wolf ID - we at T4C manage 3 Wildbook platforms: Wild North, Whiskerbook and the... |
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AI for Conservation | 3 weeks ago | |
Hi Phani,An entry point might be to participate in a challenge related to conservation on:KaggleDrivenDataFruitPunchMax Planck Institute of Animal BehaviorYou could also reach out... |
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AI for Conservation | 3 weeks 6 days ago | |
[oops, the same reply got submitted twice and there doesn't seem to be a "delete" button] |
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AI for Conservation, Camera Traps | 3 weeks 6 days ago | |
Hi @zhongqimiao ,Might you have faced such an issue while using mega detectorThe conflict is caused by:pytorchwildlife 1.0.2.13 depends on torch==1.10.1pytorchwildlife 1.0.2.12... |
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AI for Conservation, Camera Traps, Open Source Solutions | 3 weeks 6 days ago |
WILDLABS Tech Tutors: Season One
19 May 2020 12:00am
Get To Know FIT
6 May 2020 12:00am
Competition: iWildCam 2020
4 May 2020 12:00am
Training Course: Quantitative Analysis of Marine & Coastal Drone Data
29 April 2020 12:00am
Call for Submissions – Arm Research Summit 2020
24 April 2020 12:00am
WILDLABS Tech Hub: WWF PandaSat
13 April 2020 12:00am
Webinar 11PST 3/20 - Deep Learning for Airborne Tree Detection
17 March 2020 1:28am
24 March 2020 9:57am
Hello Ben. Unfortunately I couldn't make it on Friday. It would be great if I could take a look at your slides. I'm interested in trying to count mangrove trees. I have some WorldView 2 data. Do you think I could use DeepForest for this?
31 March 2020 4:21am
DeepForest docs are here.
https://deepforest.readthedocs.io/
Welcome to have a look. My experience is that individual trees cannot be distinguished in satellite imagery. The coarest resolution we've had success with is 0.3m. However, the deepforest weights may still useful as a starting location. If there are visible objects in your image that you want to detect, collecting a few hundred training data samples and retraining the model for 2-3 epochs could be useful. See the link for details. Happy to help, submit issues on the github repo is something isn't clear/doesn't work. Everything is in dev.
WILDLABS Community Call Recording: Rainforest X-PRIZE
30 March 2020 12:00am
Open, challenging dataset for audio classification
27 March 2020 10:52am
27 March 2020 11:51am
Hi Radek,
I'm sure others can help here, but check out our recent virtual meetup (it'll be posted here in about an hour), the speakers - particularly Dave Watson - shared open datasets that might be what you're looking for.
Over on Twitter, Jesse Alston is collating a google sheet so that people can advertise data sets that grad students can use to finish theses. @arik 's reply here might be of particular interest: 'We have been recording 24/7 soundscapes in remote US locations like Yellowstone NP and rural central Wisconsin with multiple GPS synced recorders. Our goal is to study wolf and coyote vocalisations, but if anyone can make use of these data for their own studies, drop me a line!.'
Hope this helps!
Steph
27 March 2020 12:25pm
Steph, thank you so much for this, this is wonderful :) Really, really apreciate you sharing this with me :) Diving into all of the wonderful resources from you, thank you so very much for this!
Radek
Help collate list of Ecology/Conservation Data Sets for grad students
27 March 2020 12:07pm
Automated species detection from camera traps
30 January 2020 8:43am
25 March 2020 2:59pm
I see. Im interested and would like to help. I will need the images to train the network. As many as possible.
if you dont have them yet, try to find similar images preferably of the same species. I will use them to test the performance of the detection.
25 March 2020 6:49pm
I'm not familiar with camera traps, but there are a couple of options:
1) If the animals tend to cover most part of the image, then you can train a CNN classifier to distinguish between species (available with the keras-Tensorflow modules in Python)
2) If, however, the animals only cover a small part of the image (e.g. in the distance), it might be better to use an object detector (I've used YOLOv2 in the past for fish detection), which however is not that straightforward, especially with Python (I used MATLAB)
In any case, keras-Tensorflow classification with Python might be the most straightforward option for your goal. You should also certainly have a look at Google's Wildlife Insights platform which is specialized for species classification from camera trap images.
27 March 2020 10:33am
This can be done, happy to help :) But I think I need to understand the situation a little bit more.
Do you already have the data for training / inference? Do you have any example images with the species in them annotated? Say a still from the camera with a tiger and a csv file referencing that file and annotating that there is a tiger in the image?
Would you like someone to do the developing and training of the deep learning model for you? I work as an AI research engineer at the Earth Species project and I am also a part of a community of deep learning practitioners where we apply cutting edge research to various problems. Here you can check a little initiative I started a couple of days ago to teach people how to work with audio (there is a related forum thread but unfortunately it is in closed forums for the time being as it is associated with a course that is under way). My main point is this - if you have the data and would like someone to help you out on the modelling part, I can coordinate this.
Alternatively, if you cannot release the data, I can point you to materials that can get you started to carry out the work yourself.
Webinar: Citizen Science Online
26 March 2020 12:00am
WILDLABS Tech Hub: Poreprint
26 March 2020 12:00am
Enter the Zooniverse: Try Citizen Science for Yourself!
18 March 2020 12:00am
Tutorial: Train a TinyML Model That Can Recognize Sounds Using Only 23 kB of RAM
16 March 2020 12:00am
Accepting Applications: ArcGIS Solutions for Protected Area Management
4 March 2020 12:00am
Competition: Plastic Data Challenge
3 March 2020 12:00am
Call for Nominations: Tusk Conservation Awards
3 March 2020 12:00am
Hawai'i Conservation Conference
28 February 2020 12:00am
Competition: The Artisanal Mining Grand Challenge
26 February 2020 12:00am
Listening to Nature: The Emerging Field of Bioacoustics
24 February 2020 12:00am
Team for Building of ML app for horse identification and conservation
20 February 2020 11:09pm
HWC Tech Challenge Update: Thermal Elephant Alert System
17 February 2020 12:00am
ICEI2020: 11th International Conference on Ecological Informatics
14 February 2020 12:00am
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11 February 2020 12:00am
WILDLABS Virtual Meetup Recording: Acoustic Monitoring
5 February 2020 12:00am
AI for camera trap public data
17 December 2019 9:20pm
A New Cloud Platform Unveils the Most Diverse Camera Trap Database in the World
17 December 2019 12:00am
[ARCHIVED] Workshop on Deep Learning Methods and Appliocations for Animal Re-Identification
25 November 2019 6:24pm
WACV2020 AI for Animal Re-ID: Deep Learning Methods and Applications for Animal Re-Identification
25 November 2019 12:00am
17 March 2020 3:52pm
Thanks Ben. I'll see what I can do.