We now have two Audio Capture Devices (ACDs) delivering encrypted audio data successfully to our CitySounds server. Interestingly, every now and again one of the ACDs loses some WiFi signal and goes dark for a minute or so — perhaps a delivery truck or other vehicle in the adjacent street is blocking the signal.
A separate server script picks up the audio data files as soon as they arrive and moves them to a separate, inaccessible file partition and re-encrypts them with a wholly separate encryption key.
So finally, we have been able to bring the full CitySounds Data Collector architecture online, and are now receiving encrypted audio data from our field test device, which is placed in a University private garden via our exernal WiFi AP mounted on the 5th floor of the Main Library.
The image above shows the 10-second audio samples (transferred via scp and separately encrypted with GnuPG) flowing through onto the CitySounds server from one of our Audio Capture Devices (ACDs). Never has a directory file listing looked so pretty!
Our Raspberry Pi based ACDs are also now fully time-synchronised through our local NTP server to ensure they work collectively and accurately to cover off each 60-second block of time. Once all six ACDs are deployed, they will each record a 10-second slice in sequence.
We are now on track to deploy to the trees in the Meadows in Edinburgh early next week: this will be a major accomplishment, especially given the additional extreme weather and strike issues we have been having to navigate the last couple of weeks.
In order to capture full audio data, we will be using the Raspberry Pi Zero W boards to send data over WiFi, and we have now installed a new WiFi Access Point to receive the data. The Access Point is located on the South West corner of the University Main Library, as indicated by the blue arrow on this map:
The photo below shows a view of the library from the Meadows, followed by a close-up of the newly installed Access Point (a small grey box).
We are looking forward to testing the reception range of the new device.
An earlier post described my initial steps in building an audio monitoring device, and over the last couple of weeks, I have worked on putting the electronics inside an enclosure that is both waterproof and will not be too obtrusive when installed in a tree. We refer to it as the “bird-box”. The box is made largely of 3mm plywood, with some thicker wood framing. It’s been stained and varnished to weatherproof it. The design enables easy separate access to change the battery without dislodging the Raspberry Pi Zero W processor and the Ultramic. On the inside, we use hermetically sealed plastic lunch boxes to hold the sensitive electronics, with sealed punch-throughs for the various connecting cables. It’s cheap and very effective.
Our next step was to carry out some field-testing of the device. We decided to do this in the private garden of a University of Edinburgh property, close enough to the Meadows to capture representative samples of sounds in the environment. I installed a temporary WiFi access point in the building to pick up the data from the prototype device in the garden, which is collected on a laptop also sited within the building.
Here’s a small sample of what we recorded over the three days of wind, snow, rain and freezing temperatures. The unit performed well in these challenging conditions, including the 30,000 mAh power bank.
This audio sample is indicative of what kinds of things we can detect in the urban environment: an emergency siren in the background, a stonemason working on a nearby building, and a snatch of bird song. The spectrogram below illustrates the different frequency ranges at which the sounds occur, from 0kHz up to 20kHz.
The bottom pink line is ambient sound.
The faint wavey pink line above that is the siren.
The strong pink fence-like pattern above that is the sound of the stonemason tapping away.
Finally, the little pink burst (between 3kHz and 5kHz) just before the last two taps from the stonemason is the clearly-audible bird song.
Listen again whilst looking at the image and you can observe how the sounds interact with each other.
We are excited to see that the recording device, the WiFi router and the computer all seem to be working together well.
We have prototyped a bio-acoustics listening device based on the Raspberry Pi Zero W and Dodotronic Ultramic. We are about to start 24hr continuous run testing in cold weather in two test sites. So far, the power consumption is pretty much as predicted considering cold weather.
A battery that delivers 30,000mAh should give 7 days continuous operation before needing to be recharged, and with a number of power saving options employed on the Pi, the initial tests have certainly borne this out. The cold weather (we have had several days of sub-zero temperatures and snow/ice) has much reduced the battery capacity, which is not surprising given the characteristics of Lithium-Polymer batteries.
Separately, we have now configured a Libelium Waspmote-based temperature, pressure, humidity sensing device to work within our existing LoRaWAN IoT infrastructure.