IoT-based construction site safety management: real-time monitoring and early warning system construction

For the goal of ensuring the smooth progress of construction, it is urgent to design a real-time construction safety management method. First, the overall architecture of internet of things (IoT) real-time monitoring is constructed, which includes sensing layer, network layer, platform layer, and application layer; second, according to the accident causation theory, the construction risk monitoring index system is determined, and the key risk features are extracted. Subsequently, the improved ReliefF algorithm is used to select important construction risk features, and the hyperparameters of the support vector machine (SVM) are optimised by the particle swarm optimisation (PSO) algorithm, and important risk features are inputted into the PSO-SVM model to obtain final risk warning results. Application results of a construction project show that the data transmission delay of the system is less than 0.2 s, and the monitoring accuracy can reach 91.31%, showing excellent real-time and accuracy.

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Publication Details

Journal
International Journal of Information and Communication Technology
Published
2025-01-01
DOI
https://doi.org/10.1504/ijict.2025.146835
Primary Topic
Risk and Safety Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

IoT-based construction site safety management: real-time monitoring and early warning system construction

Zhongxin Li, Qiaozhen Liang, Fei Ye
International Journal of Information and Communication Technology
Risk and Safety Analysis
article

IoT-based construction site safety management: real-time monitoring and early warning system construction

Zhongxin Li, Qiaozhen Liang, Fei Ye
article en

Abstract

For the goal of ensuring the smooth progress of construction, it is urgent to design a real-time construction safety management method. First, the overall architecture of internet of things (IoT) real-time monitoring is constructed, which includes sensing layer, network layer, platform layer, and application layer; second, according to the accident causation theory, the construction risk monitoring index system is determined, and the key risk features are extracted. Subsequently, the improved ReliefF algorithm is used to select important construction risk features, and the hyperparameters of the support vector machine (SVM) are optimised by the particle swarm optimisation (PSO) algorithm, and important risk features are inputted into the PSO-SVM model to obtain final risk warning results. Application results of a construction project show that the data transmission delay of the system is less than 0.2 s, and the monitoring accuracy can reach 91.31%, showing excellent real-time and accuracy.

International Journal of Information and Communication TechnologyVol. 26(21)
Anhui Business College (CN)
Anhui Provincial Department of Education, Anhui Provincial Quality Engineering Project
Openalex Percentile: Top 86%
Risk and Safety Analysis
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IoT-based construction site safety management: real-time monitoring and early warning system construction — Zhongxin Li, Qiaozhen Liang, et al. · International Journal of Information and Communication Technology (2025) | TGRS Research Map | TGRS