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An Integrated System for Real-Time Safety Helmet Monitoring and Advanced Environmental Prediction
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Author(s): Qizheng Zhu (The Hong Kong Polytechnic University, Hong Kong), Changyu Zhang (The Hong Kong Polytechnic University, Hong Kong), Zhenming Xu (The Hong Kong Polytechnic University, Hong Kong), Qinyan Wang (The Hong Kong Polytechnic University, Hong Kong), Haoting Wan (The Hong Kong Polytechnic University, Hong Kong), Aquil Mirza Mohammed (The Hong Kong Polytechnic University, Hong Kong & School of Low-Altitude Digital Intelligence, Liaoning Technical University, Huludao, China)and Cong Wu (Liaoning Technical University, Huludao, China)
Copyright: 2026
Pages: 16
Source title:
Intelligent Construction Monitoring Systems: Real-Time Safety, Environmental Prediction, and Risk Management
Source Author(s)/Editor(s): Aquil Mirza Mohammed (The Hong Kong Polytechnic University, Hong Kong)and Hewa Majeed Zangana (Duhok Polytechnic University, Iraq)
DOI: 10.4018/979-8-3373-9245-5.ch003
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Abstract
The current automatic safety helmet detection system does not include real-time environmental data such as temperature, humidity and wind speed. This information is very important for a comprehensive assessment of the risks at the work site. This study aims to combine real-time helmet compliance monitoring with an advanced environmental forecasting framework. It solves the limitations of traditional methods, which rely on manual supervision and do not include environmental data. We have created a complete cycle from monitoring to warning, using a module design connected through Internet of Things communication. It includes reliable data transmission, dynamic visualization, multi-level alerts, environmental assessment and security storage. The environmental prediction part uses wavelet decomposition to clean up noise sensor data, uses long- and short-term memory (LSTM) networks for accurate time series prediction, and Gaussian process regression (GPR) to provide probability prediction and measurement uncertainty.
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