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AI for Conservation / Feed

Artificial intelligence is increasingly being used in the field to analyse information collected by wildlife conservationists, from camera traps and satellite images to audio recordings. AI can learn how to identify which photos out of thousands contain rare species; or pinpoint an animal call out of hours of field recordings - hugely reducing the manual labour required to collect vital conservation data. The AI For Conservation group is intended to unite and inspire all WILDLABS community members—whether already involved in AI for conservation, or not—to understand how to use and/or directly contribute to open-source research and development efforts.

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How drones, AI & Open Source Software are being used to combat Alien Invasive Plants in South Africa

Alien Invasive Plants (AIP) have become a major threat to South Africa's sensitive Fynbos biome. In 2017 and 2018, fires in the Western Cape region killed 8 people and destroyed...

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Hi Ginevra, thank you! Its such a huge advantage to have tech tools available to us in conservation. Not just from an analysis point of view but also from a practical application view😊

Aloha, this is a great project. Thanks for sharing. I have been looking for ideas to integrate machine learning with some of the conservation work we are engaed in here on Kauai. Thank you

Thank you for your comment Chris! Using these tools has made a huge difference in the way we can monitor and manage Invasive Alien Vegetation. I hope you are able to integrate similar systems with your projects there. If you need any help, feel free to reach out!

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Documentary on Conservation

My name is Nick Rizzini, and I’m a London-based filmmaker currently working on a documentary focused on wildlife conservation. A section of the project aims to explore...

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Hi Nick,

At Wildlife.ai, from the other side of the world, we would be happy to chat with you. PM if interested 

Victor

 

Hi Nick!

At Birds Canada, our NatureCounts open data platform connects bird and biodiversity data with people who need it for conservation and research. In particular, our mobile app makes data collection by citizen scence and research projects more efficient, accurate, and accessible. We are happy to chat, if that aligns with your project!

Kyle

Hi Nick,

Thank you for reaching out and for the incredible work you’re doing to spotlight conservation through film. We’d be very interested in learning more about your documentary project.

At Savannah Tracking-Home - Savannah Tracking, we design and manufacture innovative wildlife tracking technologies — from lightweight GPS tags/collars for birds and medium-sized mammals, to robust satellite-enabled collars for elephants (Asian & African). Our tools are used worldwide to support wildlife conservation, research, and conflict mitigation by providing real-time movement data.

We’d be happy to connect and explore how our work might fit into the story you're telling around technology's role in conservation. Feel free to reach out to us or let us know the best way to continue the conversation.

Looking forward to hearing from you

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Smart Drone to Tag Whales Project

Hi all,Let me please introduce our project named Smart Drone to Tag Whales, awarded in WILDLABS AWARDS 2024.Our research team (@machadoams, @anakfleck, @...

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I would love to hear updates on this if you have a mailing list or list of intersted parties!

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Drone Imagery and Deep Learning enabling northern gannet counts

Using Ultra-High-Resolution Drone Imagery and Deep Learning to quantify the impact of avian influenza on northern gannet colony of Bass Rock, Scotland. Would love to hear if you know of any other similar exaples from elsewhere in the world where a similar approach was used.

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Non-Invasive Turtle Nest Monitoring Using RTI Technology

📢 We're excited to share our new #ConservationTech initiative!Using Radio Tomographic Imaging (RTI), our team is building a non-invasive system to monitor...

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Hello, could you please elaborate on what the purpose of this project is? Thanks a lot :)

 

Lukas

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Help needed : Overview of Image Analysis and Visualization from Camera Traps

As part of my thesis internship, I’m exploring ways to improve ecoSecrets – an open-access web application designed by Natural Solutions to support...

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This camera trap survey addresses the crucial need for a unified and comprehensive solution to improve data reliability and standardize monitoring techniques in wildlife research. Well done !

This survey on camera trap use is a valuable effort to improve data quality and consistency in wildlife monitoring. Looking forward to the results and how they will help shape best practices and future research. Great initiative!

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AI/ML opportunities

Hello,I’ll be graduating with a masters in AI and machine learning in August, and I’m currently doing my industry project with Aurizn, where I’m segmenting high resolution...

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Ritika, 

All the best! I hope someone provides a more substantive answer! 

I have also graduated with masters in AI and ML recently. Difference being I am at the end of my IT career. I am looking for a career switch to biodiversity, wildlife conservation, sustainability or climate change. 

I am trying to do my best to do modern job search. Just warming up to it. LinkedIn, posting relevant posts, being consistent. Virtual networking. In person networking. Being a soon to be fresh graduate, you have access to a huge student networking and academic circle. Keep hitting them consistently and I am sure you will find something. 

Share the good news when it happens. :)

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Dual-/Multi-Use Technology Strategies

Hi Everyone, I am new to the WildLabs community and relatively new to conservation technology. I have been working in this space since 2018 (marine and coral focused with NOAA),...

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That is a great point and the current international trade climate has been making supply chain even more difficult. This also deeply affects US companies given much of the US goods manufacturing and assembly happening in China. Over the last few years, I have been seeing US hardware companies (e.g. drone platform and component OEMs) sourcing their goods from India, Turkey, Canada, and more recently in African and South American nations. Because of the last 3-to-5 years of increasingly restrictive and costly international hardware trade, there has been a emergence of specialized component manufacturers internationally. For European companies interested in providing hardware services to the US, I would suggest diversifying the supply chain beyond China. Given the current climate and trends, that added supply chain resilience may be a good idea, regardless of work with the US.

This is more than the supply chain though. The point was the company itself cannot use any tech for anything from the 5x companies. So in my case my ISP is incompatible. Essentially I see the only companies making that kind of sacrifice are ones that want to devote themselves to defence only.


Of course. That’s US defense as a customer. European defence is fully on the table.


It’s just sad that it’s not restricted to defence. US government wildlife organisations cannot buy European tech unless that European company was pure in their eyes.

True, the US ecosystem is a challenging space right now, for basically all sectors. 

We should not let the US chaos prevent us from engaging with opportunities in other nations' multi-use markets. A company's ability and journey to tap into other markets is very unique to them (product, team, finances, infrastructure, agility), and some simply cannot adapt. There is no one size fits all (or even most) solution when it comes to multi-use strategies. It is important that  we are systematic about evaluating the cost to adapt our product-service to a different market, and the value of new opportunities in that new market, without losing track of underlying conservation and social good needs.

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PhD Advice

Hey Everyone!First post here. I'll be graduating soon with a Master's degree in Fisheries, Wildlife, and Conservation Biology from NC State and am looking to continue my education...

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Hi @ethanmarburger, I am probably not the best to give advice here given that it took me nearly two decades to actually finish my PhD, but I'd aim for something that you are really interested in so that you can keep up a high momentum. If you love your project you are more likely to cruise through the 'grind' periods. In terms of networking, WILDLABS is definitely a great place to start! You may well find some connections just looking across the threads here, and reaching out to people that are doing work you are interested in. More broadly, and depending on where you are in the world, you might be able to volunteer or even get some work on projects in your area, which can be a good way to get a foot in the door to larger research projects. You could possibly look at helping out on some analysis of spatial/AI datasets etc, or reach out to not-for-profits and conservation charities and see what they need/you might be able to help with - but try and be as specific as possible so they know straight away what you are after. Just a few quick ideas off the top of my head, and more than happy to discuss further. My best for your search!

Cheers,

Rob

Hi Ethan, It's indeed a competitive area. My advice for you (and anybody else seeking a PhD supervisor)...

  1. Do background research on each individual potential supervisor and always approach them demonstrating your alignment with their research focus.
  2. Show that you have read and understood one or two of their key (relevant) papers in your initial email to them.
  3. Have in mind something relevant to you AND to the potential supervisor, to propose as a topic in your initial email to them. But, remain open to their ideas - there's a good chance they have something that would align with your interests and that would (more) smoothly generate a successful PhD than you might have come up with ;-)
  4. Write clearly and succinctly.
  5. Demonstrate enthusiasm and highlight any relevant past experience and engagement in the relevant area (briefly).
  6. Attach a PDF CV.
  7. Apply for PhD positions in areas where you are qualified.
  8. Evidence that you have published a good paper, especially as first author, from your Masters thesis would be a bonus.

This is a time-consuming process. But you may end up spending 3+ years working with this supervisor, and vice versa. It's important for all concerned that you (and they) make a good, informed decision.

Good luck in your search!

Alan.

 

 

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Software QA Topics

Hi everyone,What should we share or demo about Software Quality Assurance? Alex Saunders and I, the two Software QA people at Wildlife Protection Solutions (WPS) are going to...

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Hi everyone,

What should we share or demo about Software Quality Assurance? 

Alex Saunders and I, the two Software QA people at Wildlife Protection Solutions (WPS) are going to do a community call to knowledge share on software testing and test automation in the 3rd or 4th week of January.

We've listed a few QA topics that we could talk about in this 1-2 minute poll here basketball stars and would like your feedback on topic priority.

Thanks for your feedback and we look forward to connecting! We'll also post when we have an exact date and time pinned down.

Sounds like a great initiative—looking forward to it! I’d love to hear more about your real-world test automation setup, especially any tools or frameworks you’ve found effective at WPS. It’d also be helpful to see how QA fits into your dev workflow and any challenges you’ve faced specific to conservation tech. I just filled out the poll and can’t wait to see what topics get chosen. Thanks, Alex and team, for organizing this!

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Prospective NSF INTERN 

Hello all,My name is Frank Short and I am a PhD Candidate at Boston University in Biological Anthropology. I am currently doing fieldwork in Indonesia using machine-learning...

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My name is Frank Short and I am a PhD Candidate at Boston University in Biological Anthropology. I am currently doing fieldwork in Indonesia using machine-learning powered passive acoustic monitoring focusing on wild Bornean orangutans (and other primates). I am reaching out because as a student with a National Science Foundation Graduate Research Fellowship, I am eligible to take advantage of the NSF INTERN program which supports students to engage in non-academic internships through covering a stipend and other expenses, with the only caveat being that the internship must be in-person and not remote. I was wondering if any organizations in conservation technology would be interested in a full-time intern that would be coming in with their own funding? 

In addition to experience with machine learning and acoustics through training a convolutional neural network for my research, I also have worked with GIS, remote sensing, and animal movement data through other projects. Further, I have experience in community outreach both in and outside of academic settings, as I previously worked for the Essex County Department of Parks and Recreation in New Jersey for 3 years where I created interpretive signs, exhibits, newsletters, brochures, and social media posts. Now while doing my fieldwork in Indonesia, I have led hands-on trainings in passive acoustic monitoring placement and analysis as well as given talks and presentations at local high schools and universities. 

I would love to be able to use this opportunity (while the funding still exists, which is uncertain moving forward due to the current political climate in the US) to exercise and develop my skills at a non-academic institution in the conservation technology sphere! If anyone has any suggestions or is part of an organization that would be interested in having me as an intern, please contact me here or via my email: fshort@bu.edu geometry dash. Thank you!

Hi Frank, your work sounds incredibly valuable and well-aligned with current needs in conservation tech. With your strong background in machine learning, acoustics, GIS, and outreach, you’d be an asset to many organizations. I’d recommend looking into groups like Rainforest Connection, Wildlife Acoustics, or the Conservation Tech Directory (by WILDLABS)—they often work on acoustic monitoring and might be open to in-person internships, especially with funding already in place. Best of luck finding the right match—your initiative is impressive!

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Counting Problems in Conservation

We're actively exploring new applications for CountGD, our object counting model designed to automatically count instances in images. So far, we've partnered with...

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'Boring Fund' Workshop: AI for Biodiveristy Monitoring in the Andes

Thanks to WILDLABS 'Boring Fund' support, we are hosting a workshop on AI for biodiversity monitoring in Medellin, Colombia, April 21st to 24th. This is a followup discussion to...

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Hey @benweinstein , this is really great. I bet there are better ways to find bofedales (puna fens) currently than what existed back in 2010. I'll share this with the Audubon Americas team.  

Hi everyone, following up here with a summary of our workshop!

The AI for Biodiversity Monitoring workshop brought together twenty-five participants to explore uses of machine learning for ecological monitoring. Sponsored by the WILDLABS ‘Boring Fund’, we were able to support travel and lodging for a four-day workshop at the University of Antioquia in Medelín, Colombia. The goal was to bring together ecologists interested in AI tools and data scientists interested in working on AI applications from Colombia and Ecuador.  Participants were selected based on potential impact on their community, their readiness to contribute to the topic, and a broad category of representation, which balanced geographic origin, business versus academic experience, and career progression.

Before the workshop began I developed a website on github that laid out the aims of the workshop and provided a public focal point for uploading information. I made a number of technical videos, covering subjects like VSCODE + CoPilot, both to inform participants, as well as create an atmosphere of early and easy communication. The WhatsApp group, the youtube channel (link) of video introductions, and a steady drumbeat of short tutorial videos were key in establishing expectations for the workshop.

The workshop material was structured around data collection methods, Day 1) Introduction and Project Organization, Day 2) Camera Traps, Day 3) Bioacoustics, and Day 4) Airborne data. Each day I asked participants to install packages using conda, download code from github, and be active in supporting each other solving small technical problems. The large range of technical experience was key in developing peer support. I toyed with the idea of creating a juypterhub or joint cloud working space, but I am glad that I resisted; it is important for participants to see how to solve package conflicts and the many other myriad installation challenges on 25 different laptops.

We banked some early wins to help ease intimidation and create a good flow to technical training. I started with github and version control because it is broadly applicable, incredibly useful, and satisfying to learn. Using examples from my own work, I focused on github as a way both to contribute to machine learning for biology, as well as receive help. Building from these command line tools, we explored vscode + copilot for automated code completion, and had a lively discussion on how to balance utility of these new features with transparency and comprehension.  

Days two, three and four flew by, with a general theme of existing foundational models, such as BirdNET for bioacoustics, Megadetector for Camera traps, DeepForest for airborne observation. A short presentation each morning was followed by a worked python example making predictions using new data, annotation using label-studio, and model developing with pytorch-lightning. There is a temptation to develop jupyter notebooks that outline perfect code step by step, but I prefer to let participants work through errors and have a live coding strategy.  All materials are in Spanish and updated on the website. I was proud to see the level of joint support among participants, and tried to highlight these contributions to promote autonomy and peer teaching. 

Sprinkled amongst the technical sessions, I had each participant create a two slide talk, and I would randomly select from the group to break up sessions and help stir conversation. I took it as a good sign that I was often quietly pressured by participants to select their talk in our next random draw. While we had general technical goals and each day had one or two main lectures, I tried to be nimble, allowing space for suggestions. In response to feedback, we rerouted an afternoon to discuss biodiversity monitoring goals and data sources. Ironically, the biologists in the room later suggested that we needed to get back to code, and the data scientists said it was great. Weaving between technical and domain expertise requires an openness to change.

Boiling down my takeaways from this effort, I think there are three broad lessons for future workshops.

  • The group dynamic is everything. Provide multiple avenues for participants to communicate with each other. We benefited from a smaller group of dedicated participants compared to inviting a larger number.
  • Keep the objectives, number of packages, and size of sample datasets to a minimum.
  • Foster peer learning and community development. Give time for everyone to speak. Step in aggressively as the arbiter of the schedule in order to allow all participants a space to contribute.

I am grateful to everyone who contributed to this effort both before and during the event to make it a success. Particular thanks goes to Dr. Juan Parra for hosting us at the University of Antioquia, UF staff for booking travel, Dr. Ethan White for his support and mentorship, and Emily Jack-Scott for her feedback on developing course materials. Credit for the ideas behind this workshop goes to Dr. Boris Tinoco, Dr. Sara Beery for her efforts at CV4Ecology and Dr. Juan Sebastian Ulloa. My co-instructors Dr. Jose Ruiz and Santiago Guzman were fantastic, and I’d like to thank ARM through the WILDLABS Boring fund for its generous support.    

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Animal Detect is live

Hey everyone,WE ARE FINALLY LIVE!  After 8 months of hard work with @HugoMarkoff we are ready to present the first stable version of Animal Detect!Animal Detect is ...

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Super happy to finally have Animal Detect ready for people to use. We are open for any feedback and hope to bring more convenient tools :) 

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We are releasing SpeciesNet

We're extremely excited to announce (and open source) SpeciesNet today, our AI model for species recognition in camera trap images, capable of recognising more than 2000 animals...

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This is great news!



I am using rather high resolution images and have just ordered some 4K (8MP) camera traps.

The standard megadetector run via Addax AI is struggling a bit with detecting relatively small animals (frame wise) although they have quite a number of pixels. This naturally follows from the resizing in megadetector.

I have noticed :

but this seem not readilly available in Addax AI. Is it somehow supported in SpeciesNet?

Cheers,

Lars

Hi Ștefan

In my current case, I am trying to detect and count Arctic fox pups. Unfortunately, Arctic fox does not seem to be included in the training data of SpeciesNet but even if it was, pups look quite different from adults. 

After a quick correspondance with Dan Morris and Peter van Lunteren on the Addax AI gitHub I was made aware of the image size option of MegeDetector. It seem to help somewhat to run the detection at full resolution (in my case up to 1920*1080). I have the impression that I get more good detections, but also less false detections (even without repeat_detection_elimination) by using higher resolution.

Dan offered to have a look at my specific challenge so I sent him 10K+ images with fox pups.

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