Hi everyone. I am suuuuuper late on this discussion but I just finished 6-month fieldwork deploying 18 SM Micro over 70 different locations in Java, so I thought I would like to share my opinion on this device. So my work is basically installing each recorder in one location for the duration of 7-14 days before moving it to a different location, with battery and silica gel changed in between every deployment. Here's my thought:

Waterproofing - The first 2 months of the fieldwork was the wettest season I have ever experienced in the field. Extreme rain almost on a daily basis. Most of the time the recorder was working just fine except for the 2nd week of deployment when I found the inside a bit wet, but it was probably because I forgot to ensure that both lids were clicking.  The recorder still works fine after this deployment, and this was when I decided to change the silica gel before the next deployment.

Sound quality - As mentioned by others. there's an annoying peak at 6kHz. I did not originally plan to do soundscape analysis so it wasn't a big problem at the beginning, but now there is some discussion on doing so. Other than this I found the quality to be just adequate.

Battery Life - I am using alkaline 1,5 volt (non-rechargable) battery and get ~120 hours of recording, with a sample rate of 32khz. Suitable for my method, but certainly not for longer deployment.

Safety - My field site is full of a poacher who does not like to be detected, and the rangers warned me so many times about the camera trap that was destroyed or stolen by these people. I used steel cable and a small carabiner-style padlock which I later realized wouldn't stand a chance against a few hits of the machete, but luckily no recorder went missing--mostly because I tried to hide it as far as possible from the trails and cover our tracks. The small size of SM Micro makes it easy to hide among foliage (be careful on contact noise between leaves and recording), and the fact that it is colored green and has no external light also greatly helps (unlike Swiftone. Seriously, who thought that white is a perfect color for an expensive device that will be left in the forest for a long time?)

In conclusion, it is a cheap and easy-to-get device (compared to the mythical Audiomoth) for species presence detection in a short time like I did, but certainly not for longer deployment or more intricate bioacoustic analysis. 

Hi everyone, 

I wanted to provide an update on behalf of Wildlife Acoustics regarding some of these comments in this thread. As some of you may know, we have just announced the second generation of our Song Meter Micro. Along with 33% longer battery life due to an expanded battery tray (which now holds 4 AAs instead of 3), the Song Meter Micro 2 will also have a flatter frequency response. Though we don’t have a firm release date at the moment, we are currently looking at an early 2024 release, with pre-orders likely to start at the end of 2023. Detailed frequency response charts and specs will also be posted to our site soon. In fact, we have built an anechoic chamber in our new office and will be doing detailed testing with a host of new precision instruments. For more info on the Micro 2, check out our current product page. Lastly, thanks all for your open and honest feedback. It allows us to make our products better and better for you. 

The BTO Acoustic Pipeline is free to use up to 100 GB / year (about 50 nights of triggered bat recording). I am not un-biased to comment on performance because I built the classifiers that are used by the Pipeline, but I would strongly recommend that you take a dataset (with everything - not just pulling out the best bat recordings) that you have taken time to manually check, put it through each option that you are considering, and critically compare the performance. 

In particular, the largest differences in performance between a good and more poorly performance classifier will be for some of the more cryptic species, so particularly focus on e.g. Myotis species, Plecotus species - if you are in an area where Brown and Grey long-eared bat are present. See how well the approach is able to identify multiple species if present in a wav file - is the classifier just identifying the species with the strongest calls, how well does it identify bat social calls / e.g.  is it mis-identifying Pipistrellus social calls as Nyctalus species , how well does it identify weak bat calls in noisy recordings (e.g. does it miss Barbastelle calls in recordings with bush-crickets), does it mis-identify small mammals calls as bats e.g. Brown rat calls as Nyctalus species. 

Another option for you could be Arbimon - it's free and does not require any coding/programming knowledge!