Real-Time Construction Site Noise Mapping System Based on Spatial Interpolation

Abstract

Because construction noise is one of the major factors affecting the health and safety of workers and nearby residents, it must be managed appropriately. Thus, this study aimed to map real-time noise information generated during construction using a sensor network and spatial interpolation. An optimal sensor was selected in terms of cost and performance by comparing noise measurements with an officially certified sensor in a semianechoic chamber. Field constraints that required or avoided placing the sensors were identified to secure satisfactory noise-estimation performance without interfering with fieldwork. A noise-estimation model was developed based on spatial interpolation, and its performance was evaluated in an experimental environment. The experiment was conducted in two different cases: the first case with only one noise source and the second case by adding another extra noise source. For each case, the optimal sensor combinations were found by considering the noise-estimation performance and the number of sensors installed. As a result, for the first case, the model showed an accuracy of 96.90% and a root-mean square error (RMSE) of 2.19, whereas the second case showed 97.40% and 2.31%, respectively. The noise information estimated by the model was visualized through simulation software for better field applicability. Detailed spatial and numerical noise information using the proposed system will help practitioners intuitively understand the real-time tendency of noise propagation, contributing to the determination of hot spots where reduction measures should be implemented. This information can also be used to more accurately identify workers continuously exposed to noise above dangerous levels and evaluate their actual cumulative noise exposure causing possible hearing damage. This paper presents a real-time construction site noise mapping system based on spatial interpolation. The results can be applied for three main practical purposes: (1) to provide the real-time noise level information of the entire construction site to establish effective reduction measures; (2) to evaluate the long-term hazards to workers caused by construction noise; and (3) to support prompt dispute settlement by presenting reliable data evidence such as a map of onsite noise pattern changes in response to civil complaints. These practical applications are expected to help field managers and workers reduce noise-related risks during construction and eventually support enhancing safety and productivity, two main issues with which the construction industry has struggled.