Harnessing edge computing and citizen science: A new prototype design for continental‐scale acoustic monitoring in Australia and beyond

Abstract Inadequate monitoring of biodiversity is a characteristic of conservation the world over. The potential of acoustic monitoring is compelling, although the challenges remain substantial. Effective solutions require transdisciplinary collaboration among stakeholders, a focus on open‐source development, and flexible, multipronged technical approaches. The potential to harness the power of citizen science is immense. Here, we present the first open‐source, modular, expandable multitaxon recording unit and workflow pipeline that integrates recent advances in edge processing, network connectivity, and citizen science into a single system, called BioMon. The edge computing unit uses multiple on‐board artificial intelligence (AI) models to identify environmental sounds before using the mobile phone network to send the detection audio clips to both a central data repository where summary statistics are presented and to a citizen science platform for validation. Field testing revealed that the system classified bird and frog calls in real time and stimulated high levels of citizen engagement in the verification process, providing a proof‐of‐concept prototype. Technical design features and observations relating to field deployment and levels of citizen engagement are provided. With potential to be expanded to other detection modalities (e.g. images, pollen, bushfire smoke), BioMon provides a highly effective platform for improving AI species classifiers, as well as a viable model for large‐scale, real‐time acoustic monitoring of biodiversity. We discuss several existing cooperative initiatives that could be emulated.