Hi everyone, I'm Alex, founder of ASD Technologies. I've spent years developing miniature, ultra-low-power sensors and biologging devices for medical robotics as well as wildlife and movement-ecology research — GPS and acoustic loggers, physiological sensors, and modular animal-borne tags.

We've recently merged with a global edge-AIoT company, which is letting us push more on-device intelligence — onboard ML and better connectivity — into field hardware. I'm excited about what that opens up for bioacoustics and remote monitoring.

I'm here mainly to learn from this community and to give back where I can. Happy to talk shop on tag miniaturization, ultra-low-power design, on-animal acoustics, or edge ML — feel free to reach out if any of that is useful to your work.

(For context, our work lives at https://asd-tech.com, but I'm here first and foremost to connect and contribute.)

Hey everyone, my name is Aaron and I am an aerospace engineering student from the UK. I am passionate about wildlife and conservation, and am determined to use my degree to help! I look forward to learning more about the work being done and getting to know the community!

Wow, what a great project.

This is a great project! Some comments:
RaspberryPI though accessible is not the best fit for video pipelines and AI workloads or off grid deployments:
- it lacks onboard ISP which means either software implemented ISP, distorted data or on camera non energy optimized ISP.
- it lacks any power management techniques, low power modes, etc.
- it runs from SDCard using the same one for OS, swap and data, any corruption can lead to full loss.
- it runs any AI/ML workload on CPU which is extremely non efficient and any addon accelerators such as Hailo8 add a lot to power consumption and heat dissipation representing more challenges.

The advantages are of course plenty of documentation, community and all kind of makers addons, hats, etc.

For something more realistic, real life suitable I would suggest using something based on SoC with integrated NPU such as Hailo 15, Renesas RZ/V, Synaptics SL1680, MediaTek Genio or even the I.MX8M Plus for very light AI/ML workload. All of these have variety of SBCs, kits or even standalone smart camera oriented designs available from different vendors.

Hey Garin, how are you?

you should contact https://wildlifedrones.net/ they have rented the equipment (payload and drones) in the past to track pangolins, bats and many other species. But I've heard the they are closing bussiness since Trump's budget cut in the USA since this country was their first client. But I think that they may help you out getting in touch with you with the researchers.

My tech advices are, what's the species? weight? attachment method? how long do you want to track? you should use the higher LOS of the transmitter, 40 Km LOS (Line of Sight) is the higher and since you are interested in tracking fossorial species, the LOS will be affected by the obstacles (ground density, forest density, topography etc), so the LOS will be like 5% up to 10% in the field, its about 200 mt up to 4 Km

Also try contact 

https://www.apicalis.com/

If you are trying building up your payload and drone here's a link that may help you out

https://uavrt.nau.edu/

https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.13261

Hi Jérémy,

I'm the developer of the UAV-RT system. We haven't updated our website in a long time and have made some significant progress. I've got a student making updates right now. 

We've recently deployed the system in the UK on pine martens, with painted dogs in Zimbabwe, and tracking kiwi in New Zealand. Our recent deployments are showing detections far beyond ground telemetry.  I'm actively looking for some more fieldwork opportunities for the coming year and have travel money left on my grant. Feel free to shoot me an email at [email protected]. 

Have drone. Will travel. 

-Michael

For reliable bat tracking in France and Western EU, look into SigFox enabled tags. For example these are today's smallest and lightest SigFox tags with Atlas Native support so you'll get a location in addition to basic telemetry: https://asd-tech.com/product/fx05-uwasp/

@hikinghack that's a complete update!

A lot of compassion regarding the budget situation, especially knowing how great @briannaljohns is.

It’s great to see a clear plan for the hardware development! I hope you'll have nice outcomes from it! 

On the microcontroller approach for power gating the Pi — this is a well-proven pattern and worth doing even if the idle power is already low, because it also gives you a hardware watchdog for free.

The typical architecture is a small ultra-low-power MCU (STM32L0, SAMD21, or even an ATtiny) that stays awake in stop mode drawing a few microamps, handles the RTC wake-up schedule, and drives a P-channel MOSFET or load switch to cut power to the Pi entirely. When the Pi is done with its task, it signals the MCU via a GPIO line and the MCU cuts power and goes back to sleep. The key advantage over software sleep is that even a hung Pi gets cut off at the next scheduled cycle — no manual intervention needed in the field.

For the Mothbox use case where the Pi might sit idle for weeks, even 10mA idle current adds up to about 168mAh per week — enough to matter for a solar-charged system during a cloudy period. A properly gated system can get standby down to under 1mA including the MCU and RTC.

One practical note on the integrated PCB direction — if you're planning to integrate the MCU on the same board as the Pi interface, make sure to include a dedicated programming header (SWD for STM32, UPDI for modern ATtiny) so the MCU firmware can be updated in the field without disassembly. It's a small thing that saves a lot of frustration during deployment.

Happy to share more detail on the power switching circuit if useful.

Hi, are you looking to import these? Do you have any import tax considerations? This could impact which models you buy. I have been using Acorn models, very reliable and provide photo and 4K video with sound options.

Best wishes

Susan

looking forward to this discussions too. Exploring the use of sparrow and in case our use case succeeds, we'll share feedback too.

Ok

The process begins 😂

Great guide — this is exactly the kind of resource the community needs. A few additions from a hardware embedded perspective that might be worth including:

On PIR sensors — the standard Fresnel lens + PIR combination has a fundamental limitation in hot environments: when ambient temperature approaches body temperature (~35°C in African savannah), the thermal contrast between the animal and the background drops dramatically and trigger reliability degrades. This is worth calling out explicitly for tropical and arid deployments, where the standard PIR may miss animals during the hottest part of the day. Some teams have moved to passive radar (Doppler microwave) as an alternative trigger for hot environments — less species-selective but more temperature-independent.

On power architecture — one thing I'd add to the component deep-dive is the power switching circuit. Most commercial cameras use a simple battery holder with no protection. For DIY builds, a proper battery management IC with overcurrent protection, low-voltage cutoff, and reverse polarity protection adds almost no cost but prevents a lot of field failures, especially when using lithium primaries in extreme temperatures.

On IR illumination — the choice between 850nm (faint red glow, better image quality) and 940nm (truly invisible, lower image quality, shorter range) is well covered in most guides, but what's often missed is thermal management of the IR LEDs themselves. High-power IR LEDs run hot and can significantly raise the enclosure temperature in a sealed housing — worth mentioning as a factor in enclosure thermal design, particularly for cameras that run night-long video.

On the shift away from hardware — curious what drove that decision. Was it the enclosure/thermal challenges, the PIR reliability issue, or something else entirely?

Thank you for sharing.

HI

This what I am trying currently todo

https://wildlabs.net/en/discussion/looking-collaborators-ai-powered-backyard-bee-monitor-citizen-science?language_content_entity=en

I have already some algorithms and some monitoring set up in development

feel free to reach me maybe we could join forces

Hi Barbara. 

If you are able to power the Audiomoth externally from a lithium-ion source, the lithium-ion batteries can be used down to -20 deg C. They can't be charged below 0 deg C though so if you were thinking of a solar charging setup as well, then you'd need to look at the temperature range you're planning to use them in. 

In regards to the battery life for continuous recording, I found this information from here:
 

The recording lifespan of the AudioMoth on one set of batteries has previously been measured only for a subset of the possible configuration settings. Hill et al. reported the battery life of the AudioMoth using 3000 mAh lithium batteries for some common configurations [15], reporting that an AudioMoth could record for 115 days recording at 8 kHz, the lowest sample rate, for 30 s every 5 min. The developers also reported the AudioMoth lasted 9 days recording nonstop at a 48 kHz sample rate. While the AudioMoth configuration app provides estimates of battery life for any chosen configuration settings, these estimates have not to our knowledge been validated empirically.

Even derating the battery life by a factor of 2 due to cold temperature conditions would seem to get you over the finish line. One experiment you can try is to record continuously in a refrigerator and look at the recording duration. Typical refrigerators are around 2 deg C which could approximate conditions you mentioned. 

If you will be using stock Audiomoths with no modification for rechargeable batteries, then I'd recommend using Energizer Lithium AA batteries which have some of the highest battery capacities for disposable batteries. Those are airplane safe if they go in your carry-on luggage. 

Hope that helps.

Akiba