Real-Time Construction Site Noise Mapping System Based on Spatial Interpolation
Publication: Journal of Management in Engineering
Volume 39, Issue 2
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.
Practical Applications
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.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research was conducted with the support of the National R&D Project for Smart Construction Technology (No. 22SMIP-A158708-03) funded by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land Infrastructure and Transport. This work was also supported by the Korea Institute for Advancement of Technology (KIAT) grant funded by the Korean Government (MOTIE) (P0008475, Development Program for Smart Digital Engineering Specialist).
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Information & Authors
Information
Published In
Journal of Management in Engineering
Volume 39 • Issue 2 • March 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: May 25, 2022
Accepted: Oct 31, 2022
Published online: Dec 29, 2022
Published in print: Mar 1, 2023
Discussion open until: May 29, 2023
ASCE Technical Topics:
- Analysis (by type)
- Business management
- Construction engineering
- Construction management
- Construction sites
- Employment
- Engineering fundamentals
- Environmental engineering
- Geomatics
- Labor
- Mapping
- Measurement (by type)
- Noise pollution
- Occupational safety
- Personnel management
- Pollution
- Practice and Profession
- Public administration
- Public health and safety
- Safety
- Sensors and sensing
- Spatial analysis
- Spatial data
- Surveying methods
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