The thermal camera can catch micro expressions much better than what you would catch with a flash if the animal is close enough and the resolution is sufficient. If that is a important enough. That been my experience with the videos we have captured.  We also have 1280x1024 thermal. There is typical no motion blur with that.

As to how an animal would act under continuous surveillance with one of our cameras I cannot say. That experiment has never been done with our gear before. There are variety of fixed lens available. The lens I’ve shown are general purpose reasonably wide angle lens. But if you wanted to study behavior from much further away there are lens to observe from very far. They are just expensive of course.

The modules we use have impressive onboard image processing that really bring out the details. Unlike ones I’ve seen before.

Have a look at the videos on our channel and see what you think. The earliest video on the channel is in 1280x1024.

https://youtube.com/@wildlifesecurityinnovations

The thermal modules that we use with our system are quite new and I've used a lot of thermal gear over the years and none had images as good as these ones. As to suitability for behavioral research I can see that there is much more detail available with this gear than what I see with flashing traditional gear. But I'm not a behavioral researcher in the field. So the suitability would ultimately be up to the researcher themselves. But never before was there a 1280x1024 thermal camera available for use in behavioral studies, so the suitability thereof has never been evaluated before.

What resolution, age was the thermal gear you used before ? And what distance were you filming at ?

I'll definitely check out your channel! To be honest, I'm much more on the animal science and behaviour side of things than the hardware engineering side, so I can't speak to the exact specs of the older gear I've seen, but having that high of a resolution without motion blur definitely sounds like a massive leap forward.

The way I see it, the trickiest part about any remote tech, no matter how high-res it gets, is that you can never truly measure the 'avoidance factor' from behind the lens. If a cautious animal senses a foreign object in its home ground and decides to completely steer clear of that zone, the camera will never catch it. You only ever get data on the animals that don't mind the camera, which can unintentionally skew the behavioural picture.

It’s the classic observer dilemma. It’s why some of the most famous animal behaviourists in history only truly understood nuanced behaviour by actually embedding themselves in the environment and becoming part of the pack, rather than relying solely on a fixed lens. But as a tool to bridge the gap where humans can't go, it's definitely exciting to see how much clearer the visibility is getting!

I would love to have feedback from a behavioral researcher. When I made the comment, I was mostly thinking about macro behavior. I haven't dived into the requirements for micro research, but it sure is interesting.

The area where I hope to make the most impact is in human-wildlife conflict mitigation. I would be thrilled if it turned out to be useful to behavior analysis as well.

Occasionally we get a close close up of an animal. Such as this hare. I would love to know whether in you consider it contains sufficient detail for behavioral purposes.

Hare closeup in Thermal

And here, even better

Ring side view of a hare close up

Over time, the animals do get comfortable with our gear. I'm sure that a bird built a nest under the panel recently. I just haven't been out there in a while to check, but it keeps flying up from below in the area. We have a visible view of that.

Baby bird living under a solar panel

Most of our wolf videos are on our other channel. Here the wolves indeed were very wary of the gear at first. Mostly they would glance up, however at first they would have been looking at the camera, but over time I think that most of the time they were looking across the field to the road on the other side.

We also have a 4K ultra low light camera that we were lighting with invisible (940nm) lighting. This we have also recording continuously.

Wolf with 4K ultra low light camera
 
We custom design all weather enclosures for out thermal modules. They are design such if you wanted you could remove them and use them in a stealth custom made enclosure of your own. They are USB based modules, so the main recording unit can be hidden away from the camera. Here is a photo of a 640x512 unit

There's a camera mounting fitting underneath so you can can ball joint camera mounts to mount them on and only a little bit sticks up into view.
 
The 1280x1024 resolution module is a bit bigger

That would be an incredible addition to Sparrow Studio! You are free to fork the repo and add to it, and through a pull request we can even fold it into the one we're developing. 

These are very helpful information, Kim. Also, we are moving away from Jetson Nano to Raspberry Pi 5 and Pi zeros. We have made a dedicated inference engine for these devices. Now, we can run megadetectorv6 (Yolov11 models) on the pi zero, and two Resnet18 models concurrently on the pi zero. I am specifically mentioning the pi zero here because it is the lowest level hardware we are working with, and it only cost ~20 usd. With two resnet18 and 4 threads, the power consumption is around 4-5W. If we are only using 2 threads, it is 2.8W. These data make the application of these lower end chips very feasible in the field. We have recently put a pi zero 2W sparrow on a bouy with gsm. the average power consumption with all sensors and modem together is around 7-9W. In terms of Pi 5, except for transformer based models, we can run most of the CNN models with a efficient power load.

@carterjandrew These are really good questions. For now, we do not have an independent website for Sparrow. The Linkedin page in my previous post is the best place for now. That is our main communication channel for updates and progress of projects like Sparrow, MegaDetector, and PytorchWildlife. Please follow us there. 

In terms of deforestation, we do have plans to add this functionalities in the future because we have a line of work specifically on deforestation assessment under the Project Guacamaya initiative. It will be very similar to the overhead animal detection professing but on forest segmentation. 

For people sharing thoughts, we will ask some of our partners who are currently using Sparrow to share some public feedback to us. It will also likely be on Linkedin. Please keep an eye on it. 

In terms of tooling, we are designing Sparrow to be as tool agnostic as possible, so it is reduced down to a simple data collection, management, and processing platform. How data are collected, managed, and processed is totally up to different users and projects. That's our end goal. 

Same as our software. We are it to be as open and extensible as possible. We want people to be able to create their own "Sparrow Studio" on top of our base Sparrow Studio. Once it is open sourced, it should be possible. 

Please let us know if there are any questions, and feel free to send us emails. Thanks! 

Elionai - your point about lessons from past deployments and "what tends to fail first" really resonates. I think that gap between ideal-condition performance and what actually holds up in the field is one of the most underrated questions in this whole space.

I'm building something that integrates environmental monitoring, so I'd love to pick your brain on the edge/deployment side. Messaging you to connect!

That is so cool! Love the video! 

Hey Luke,

Appreciate your reply, very much.

I am not quite sure what you mean by setup but, this is the experimental design.

I will deploy cameras in shade forest areas to record insect visitors to animal feces. The “baits” will be deployed in a flat square with a camera pointing down on it at a distance of 30 to 40 cm.

So, following your comments if PIR doesnt work what should I use? Motioneyes? Or something else?

My comments regarding the battery are related to the PI shutting down when the battery level is low and some hats just stop supplying power automatically instead of being in standby/hold. So I wonder if I could do something coding/physically to solve it. Can I?

Following your advice about the fixed lens, I would need to adjust the focus for each camera in the field to ensure everything is in focus, is that right? It's a little different than a month trap since the surface where the insects will move around is not exactly even, hence my thoughts on using a autofocus camera.

Once again thanks for the help, and congrats on your elegant project.

In case someone. Find this totally out of place commemt… this is how I solved it, I've decided to use a IMX477 HQ Camera, building a *manual, heavy-duty optical rig* utilizing C/CS-mount lenses and physical macro extension tubes.

@annavallery here's the article with geospatial-ish highlights in case you're interested: https://wildlabs.net/en/article/wildlabs-geospatial-group-ictc-2026. Let me know if you have any questions or specific interests. Happy to share further details!

I'll be there for the Unconference- looking forward to it!