Rakhshan, DavisDavisRakhshanBublitz, LucasLucasBublitzKulau, UlfUlfKulau2026-09-162026-09-162026-08-2722nd Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2026https://hdl.handle.net/11420/64883Passive Acoustic Monitoring (PAM) enables continuous, non-invasive observation of wildlife and is widely used for biodiversity assessment. Long-term deployments require sensing platforms that are reliable, energy-efficient, affordable, and flexible for future extensions such as embedded inference.This demo paper presents a real-time bird detection system built around a modular embedded acoustic sensing platform for low-power environmental audio recording. The live demonstration shows the workflow from acoustic acquisition to automated BirdNET-based species inference. Bird vocalizations are recorded by the sensing platform, transferred to a connected host system, and analyzed using BirdNET to visualize detected species, confidence values, and temporal activity patterns in real time.The demonstration showcases an end-to-end low-power bioacoustic monitoring workflow, combining autonomous environmental audio acquisition, embedded sensing hardware, and real-time BirdNET-based species inference within a compact modular platform.enaudio systemsBiodiversitydata acquisitionedge AIlow power electronicsmicrocontrollerswireless sensor networksTechnology::621: Applied Physics::621.3: Electrical Engineering, Electronic EngineeringConference Paper10.1109/DCOSS-IoT69657.2026.00065