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A Python-Based AIoT Simulation Platform for Multi-Parameter Construction Safety Monitoring: An Educational and Research Tool
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Author(s): YuFeng Chen (The Hong Kong Polytechnic University, Hong Kong), ka kin Leung (The Hong Kong Polytechnic University, Hong Kong), Shing Hong Kwok (The Hong Kong Polytechnic University, Hong Kong), Hoi Shun Chau (The Hong Kong Polytechnic University, Hong Kong), kam on Kong (The Hong Kong Polytechnic University, Hong Kong)and Haozhe Ruan (The Hong Kong Polytechnic University, Hong Kong)
Copyright: 2026
Pages: 38
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.ch009
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Abstract
Construction sites face critical safety challenges from environmental hazards, structural risks, and PPE non-compliance, yet traditional manual monitoring remains inefficient and error-prone. This paper presents a Python-based Smart Construction Monitoring Simulator demonstrating AIoT principles for comprehensive safety management without physical infrastructure. The simulator integrates six modules: sensor data simulation (temperature, humidity, structural strain, PPE compliance), MQTT communication, threshold analytics, real-time visualization, intelligent alerting, and logging. Systematic validation demonstrates 94.12% detection accuracy, 96.3% environmental alert precision, and stable 72-hour operation processing 259,000 data points. The modular architecture enables rapid prototyping and serves as an educational platform, demonstrating that simulation effectively replicates real-world AIoT workflows while supporting machine learning, cloud integration, and robotic extensions.
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