I eagerly await further information about the progress of this type of technology and its availability. I am a wildlife veterinarian with experience in handling and capturing wild carnivores, and this type of device would certainly facilitate epidemiological monitoring of elusive and logistically difficult-to-handle wildlife species. Greetings from Chile!

Hi Stephanie,

It’s great to hear about your exciting work and that you’ll be attending ICCB 2025 — congratulations on presenting!

The Savannah Tracking team is participating at the exhibition, and we’d love for you to stop by our booth 15.

Given your previous interest in collaring domestic dogs and collecting high-resolution GPS data, it might be a great opportunity for us to connect in person and dive deeper into how our lightweight collar solutions — like those currently deployed on Dingoes — could support your project. We'd be happy to show you how our satellite-enabled collars work, demo our data platforms, and explore a potential fit for your needs.

While the United States remains the most represented individual country in terms of project locations, North America as a region ranks fourth overall in the total application pool. This suggests a broader geographic spread and greater participation from a wider range of countries.

Notably, only two African countries appear in the top 10 list below despite the fact that Africa is the region with the highest representation. This shows that projects based in Africa were distributed across many different countries rather than concentrated in just a few.

As shown below, of the 1,446 team members listed in applications 42.4%, identify as women. While this falls short of our target of at least 50% female representation, it marks a 12.4% increase from last year, an encouraging sign that we are moving in the right direction

This aligns with findings from our State of Conservation Tech reports, which highlight that women remain underrepresented in the sector. However, this year’s data suggests a positive shift may be underway.

Due to several factors, such as accessibility, cost, and the ease of adapting technologies from other fields (e.g., drones developed for military use), available conservation technologies are currently better suited to terrestrial environments, giving terrestrial applicants a wider range of tools to choose from. In contrast, underwater environments present unique challenges, including the need for waterproof equipment and the difficulty of transmitting data through water.

As a result, marine and freshwater research and projects remain underrepresented in the conservation technology space. This is reflected in our current application pool, where terrestrial projects account for 70.4% of submissions. This imbalance highlights the urgent need for greater investment in marine and freshwater conservation technologies, which are equally important to the future of biodiversity protection.

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

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

Read "NatureCounts - NatureCounts" on

NatureCounts - NatureCounts

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

Lively and informative discussion, I would very much like to contribute if there is some active development work with regards to this. 
I have recent experience with using Model Context Protocol (MCP) to integrate various tools & data repositories with LLMs like Claude. I believe this could be a good idea/path whereby we can do the following:
1. use the images & labels along with any meta-data, chunk/index/store it in vector db
2. integrate with existing data sources available by exposing the data through MCP server

3. Use MCP friendly LLM clients (like Claude) to query, visualize and do other open-ended things leveraging the power of LLM and camera trap data from various sources. 
 

Regards,

Ajay

Hi Jeremy,

I am copying here a reply from Juliane Röder, who is not on the forum here:

The GFBio VAT tool seems to do all the desired analysing and visualising stuff - but it isn't specialized on camera trap data. Instead, it harvests GBIF, GFBio data centers, and environmental data that you can combine in any way you want: https://vat.gfbio.org/#/

6:01

Documentation with some example code and notebooks is here: https://docs.vat.gfbio.org

6:04

A standalone tool for camarea trap data and images is nice, but maybe joining forces and adding some functionality to the VAT tool to better handle camera trap data would be a more sustainable solution...?

The VAT tool can give you some simple statistics of the chosen data (e.g. occurences of wild cats in central Europe in winters 2000-2015), and some simple analyses (wild cat occurences and snow depth). It's focus is on geospatial analyses of occurrence data. They do not have any functionality specific for camera trap data - yet.

My point was, that if you want geospatial analyses and/or additional data to compare to camera trap data, you probably don't have to build a new tool.

I'm not involved with the development of the VAT tool, but I could help with the contact. I know the VAT team.

You can contact her on juliane.roeder@uni-marburg.de.

I did a quick exploration of the VAT tool. It is built quite differently, and my first impression is that it is less accessible; however, as you become more familiar with it, you discover a wide range of options to explore for DwcA occurrences.

I believe it is extremely valuable to also have a tool that works directly with the richest data (Camtrap DP), rather than relying on translated data (Darwin Core), where important details and data structure are lost.

I also think the goals of both tools are different: map-based analysis vs. exploration.

But still usefull to get to know about each other :-)