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Intelligent acoustic monitoring made accessible

Motivation & Background
Traditional vision-based wildlife monitoring methods are limited by weather conditions, the camera’s field of view, the size of target organisms, and their proximity. There is great room for alternative technologies which can monitor wildlife more reliably through other channels: like acoustic monitoring.

Acoustic monitoring offers a reliable, low-cost, and scalable alternative to monitor wildlife, with the added bonus of detecting harmful human activity: whilst poaching and logging may be impossible to see, they are much easier to hear.

Of course, acoustic monitoring is not a new idea. However, most products only record; they don’t analyze. This gives rise to huge quantities of raw data which exceeds the manpower of researchers to analyse individually. Currently, conservation organizations often turn to big tech companies to process their raw data. Not only does this place conservationists in the passive with a big focus on historical data, but it also presents a significant barrier for small-scale, local conservation efforts. Moreover, this also hinders the potential for acoustic monitoring systems to act as alarms.

Agouti: Our Product
In light of these considerations, Agouti is an intelligent, weatherproof acoustic monitoring device that can be easily deployed for the recording and analyzing of audio data.

We employ edgeML to automatically tag the microphone data for key event classes like insect sounds and birdsongs, human activity (e.g. vehicles), and logging (e.g. chainsaw noises), storing these tags together with their respective audios for human inspection. We also record readings from temperature, humidity, and light sensors to link audio with the real world, quantifying exactly how the environment affects species’ behaviours.

Agouti broadly addresses “Challenge 2: Wildlife/Biodiversity Conservation”. Specifically, we tackle two issues at once:

Non-intrusive monitoring of endangered wildlife: Our acoustic recording system takes periodic 5-second recordings of its surrounding soundscape, which is then analysed and stored together with the audio.
Human-wildlife conflict prevention/mitigation: by examaning audio for sounds of suspicious activity (like logging or transport noises), we can detect for illegal activities detrimental to the environment.”

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