Transitioning to Proactive Safety 4.0: Leveraging Telemetric Big Data for Dynamic Noise Exposure Assessment in Marble Quarries

Traditional occupational noise risk assessment in quarries relies on static annual averages, failing to capture exposure peaks driven by operational shifts. Although noise risk assessment is a strict mandate under European Directives, capturing real-world operational volatility would require continuous, unfeasible phonometric campaigns. This study addresses this limitation by developing a dynamic, telemetry-driven energetic model to map occupational noise exposure and fleet volatility within the Carrara marble basin. The framework integrates continuous tracking from Internet-of-Things (IoT) platforms over a full calendar year with targeted in-cabin phonometric data. The empirical results reveal a dual-directional acoustic divergence from manufacturer specifications due to real-world quarry conditions and automated engine sub-regimes. Energetic tracking uncovers extensive exposure variance across production weeks; during peak periods, the skid-steer loader breaches statutory action boundaries, reaching a critical exposure value of 84.2 dB(A). Ultimately, this framework fulfills regulatory requirements through a streamlined, low-cost approach, providing a significantly more reliable and realistic hazard tracking tool than traditional static models.