Lightweight edge AI approach for real-time audio-based machine health analytics on ARM cortex-M microcontroller
Most audio-based machine-health studies on the MIMII benchmark stop at simulation, and existing edge-oriented anomaly detectors remain too large (8–64 MiB) for microcontroller deployment—leaving open the question of whether an accurate detector can actually run on a low-cost ARM Cortex-M device. This paper addresses th...