Current Research

Active Noise Control for Construction Site Noise Reduction Using Adaptive Filtering

Construction sites are environments fraught with hazards due to heavy machinery, multiple work processes, and complex environmental factors. Noise is a fundamental physical element of the work environment and is closely correlated with worker fatigue, stress, and safety incidents. Nevertheless, traditional construction safety management has primarily relied on post-incident inspections or regulatory compliance, while continuously generated noise and operational behavior data have remained underutilized.

This study aims to reinterpret construction site noise not merely as an environmental pollutant, but as an informational signal reflecting site conditions, worker burden, and potential risks. Site noise fluctuates in response to changes in work processes, equipment operation, and worker behavior, making it a useful indicator for early detection of hazardous situations. However, practical site constraints limit the repeated execution of complex signal transformations and interpretations.

Accordingly, this study proposes a model that quantitatively analyzes onsite risk factors and assesses occupational stress and risk levels by applying signal processing and data analysis techniques to noise and work behavior data. Furthermore, it aims to establish a continuous safety monitoring system and ultimately contribute to a data-driven construction safety management framework capable of proactive risk prediction and decision-making support.