Tropical forests are the most biodiverse regions on earth, providing a rich habitat for thousands of species of animals and plants. Monitoring the wildlife living within these areas is essential for scientists studying the effect of human pressures on the health of ecosystems, as well as to ensure the conservation of rare species.

Traditionally, biodiversity monitoring has been done manually by highly skilled specialists who are trained to recognise animals within the forest by sight or sound. Over the course of months and years, it is possible to build up a comprehensive list of all the animals found at a given location in the forest. Whilst this is a tried and tested method, it is expensive, slow, and susceptible to human biases.

Professor Rob Ewers and team were awarded a NERC Technology Proof of Concept grant in 2014, which developed a continuous 24-7 biodiversity monitoring system based on the automated processing of acoustic data. This was estimated to provide a saving of 98% compared to traditional human-based biodiversity monitoring while simultaneously increasing the diversity of species being monitored. This grant did not accommodate impact activities and therefore Professor Ewers successfully applied to the NERC IAA to (1) transmit the acoustic record and diversity metrics to the public via an internet radio channel; and (2) use the continuous acoustic data to monitor biodiversity. The funded activities fell into three categories: (1) engaging the global community of amateur biodiversity enthusiasts with NERC-funded science, specifically; (2) providing a platform for the audience to interact with the science; and (3) developing a prototype biodiversity monitoring system that could be deployed elsewhere in the world.

Following the NERC IAA funding, the internet radio station was launched. Following extensive testing, the hardware design and software were made fully open-source with step-by-step instructions on how to create these devices for tackling ecosystem monitoring , and an additional prototype algorithm was developed for identifying the calls of Bornean gibbons .