The vastness that makes the Amazon rainforest so diverse and fertile also makes it extremely difficult to protect. Rainforest Connection is a project started back in 2014 that used solar-powered second-hand phones as listening stations that could alert authorities to sounds of illegal logging. And applying machine learning has supercharged the network’s capabilities.
The original idea is still in play: modern smartphones are powerful and versatile tools, and work well as wireless sound detectors. But as founder Topher White explained in an interview, the approach is limited to what you can get the phones to detect.
Originally, he said, the phones just listened for certain harmonics indicating, for example, a chainsaw. But bringing machine learning into the mix wrings much more out of the audio stream.
“Now we’re talking about detecting species, gunshots, voices, things that are more subtle,” he said. “And these models can improve over time. We can go back into years of recordings to figure out what patterns we can pull out of this. We’re turning this into a big data problem.”
White said he realized early on that the phones couldn’t do that kind of calculation, though — even if their efficiency-focused CPUs could do it, the effort would probably drain the battery. So he began working with Google’s TensorFlow platform to perform the training and integration of new data in the cloud.