Internet of Things-based Acoustic Detectors for Proactive Monitoring of Threatened Forest Fauna

The project will address the issue of automatically monitoring multiple threatened forest species in real time. Current machine learning approaches process acoustic data collected offline, requiring large amounts of resources and incurring long delays in taking effective decisions. This project will develop a prototype novel low-powered wireless acoustic monitoring device for deployment in production forests to automatically detect and report on the presence and activity of threatened species, which will allow near-continuous monitoring. This will enable collection of multi-year conservation and forest management data at substantially reduced cost and assist in minimising environmental impact of commercial forestry.