The Many Reasons For Putting Microphones In Rainforests

November 30, 2024 by Maya Posch 8 Comments

If a tree falls in a forest with nobody around, does it make a noise? In the case of the rainforests equipped with the Rainforest Connection’s Guardian system someone most assuredly will.

Rainforest Connection’s Guardian system up close, with microphone visible. (Credit: RFCx)

Originally created by the people behind the US nonprofit Rainforest Connection (RFCx) using upcycled smartphones to detect the sounds of illegal logging, their project now has grown into something much larger, keeping not only tabs on sounds of illegal activity, but also performing bioacoustic monitoring for scientific purposes.

Currently active in ten countries, the so-called Guardian Platform no longer features smartphones, but custom hardware inside an IP66 weatherproof enclosure and a whole range of communication options, ranging from cellular bands to satellite communications. The petal-shaped solar panels provide the module with up to 30 watts of power, and double as a shield to help protect it from the elements.

Not only is the real-time microphone data incredibly useful for rangers trying to stop illegal logging, it also provides researchers access to countless hours of audio data, which will require detailed, automated analysis. Even better is that if the audio data is available to the general public as well, via their Android & iOS apps (bottom of page), just in case you wanted to hear what that sneaky wildlife in the jungle of Peru is up to right now.

Training Bats In The Random Forest With The Confusion Matrix

November 21, 2019 by Pat Whetman 4 Comments

When exploring the realm of Machine Learning, it’s always nice to have some real and interesting data to work with. That’s where the bats come in – they’re fascinating animals that emit very particular ultrasonic calls that can be recorded and analysed with computer software to get a fairly good idea of what species they are. When analysed with an FFT spectogram, we can see the individual call shapes very clearly.

Nyctalus noctula (noctule bat)

Myotis nattereri (natterera’s bat)

Plecotus auritus (brown long eared)

Pipistrellus pipistrellus (common pipistrelle)

Creating an open source classifier for bats is also potentially useful for the world outside of Machine Learning as it could not only enable us to more easily monitor bats themselves, but also the knock on effects of modern farming methods on the natural environment. Bats feed on moths and other night flying insects which themselves have been decimated in numbers. Even in the depths of the countryside here in the UK these insects are a fraction of the population that they used to be 30 years ago, but nobody seems to have monitored this decline.

So getting back to our spectograms, it would be perfectly reasonable to throw these images at a convolutional neural network (CNN) and use an image feature-recognition strategy. But I wanted to explore the depths of the mysterious Random Forest. Continue reading “Training Bats In The Random Forest With The Confusion Matrix” →