Advancing bioacoustic monitoring: implementing acoustic indices and sonotyping methods in artificial ecosystems with IoT–integrated data dashboards

Urban environments increasingly rely on artificial ecosystems to support biodiversity, yet effective, scalable tools for monitoring ecological health in these areas remain limited. This study introduces a Soundscape Management System (SsMS) designed to address this gap by integrating an Internet of Things (IoT)-based Automated Recording Device (ARD) with a modular data dashboard for continuous acoustic monitoring. The ARD monitors and transmits soundscape data in real time using a solar-powered, weather-resistant setup. The dashboard enables users to visualise recordings, perform sonotyping and compute key acoustic indices that reveal temporal and spectral soundscape patterns. The system was validated using data from Wanagama Forest using six acoustic indices: ACI, BIO, ADI, AEI, NDSI, and H across day-night cycles. Two indices – NDSI and Acoustic Entropy (H) – were prioritised for their ability to differentiate biophonic and anthropogenic influences. A dawn soundscape dominated by biophony (82.74%) exhibited high ACI (1995.83), strong BIO (17.117), concentrated spectral energy (ADI = 1.917, AEI = 0.403) and near-maximum NDSI (0.993), indicating rich biological activity with minimal disturbance. The SsMS offers a scalable, non-intrusive approach for tracking biodiversity in artificial ecosystems. Planned improvements include the incorporation of automated sonotyping and expert-guided classification to enable more sophisticated environmental evaluations and support conservation strategies.