Real-time acoustic monitoring system developed within the ANR LIGHT-SWIFT project. It combines embedded signal processing, on-device inference, and wireless notification paths to classify industrial sounds with low latency on ultra-low-power hardware.
Industrial IoT sensing platform for predictive maintenance on rotating assets. The system combines multi-physics acquisition, embedded anomaly scoring, and hybrid local and remote connectivity to surface machine health signals before failures occur.
Distributed acoustic monitoring project focused on urban sound quality assessment. The work combined low-power wireless nodes, embedded DSP, and environmental measurement logic to support city-scale observation and mapping.
