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Comprehensive Modeling of Occupational Diseases Using Digital Twins: An IoT-Based Approach

Comprehensive Modeling of Occupational Diseases Using Digital Twins: An IoT-Based Approach
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Author(s): Fei Qi (Laizhou Center for Disease Control and Prevention, China)and Joseph K. H. Wang (Shenzhen Babel InfoTech Co., Ltd., China)
Copyright: 2025
Pages: 38
Source title: AI-Powered Digital Twins for Predictive Healthcare: Creating Virtual Replicas of Humans
Source Author(s)/Editor(s): Balasubramaniam S. (Kerala University of Digital Sciences, Innovation, and Technology, India)and Seifedine Kadry (Lebanese American University, Lebanon & Noroff University College, Norway)
DOI: 10.4018/979-8-3373-0538-7.ch008

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Abstract

This chapter focuses on the application and beneficial effects of digital twins in the field of occupational disease prevention and treatment. Taking the IoT approach as an example, this chapter introduces how to use both factory site data and worker physiological data to build digital twins and provide personalized prevention and treatment models through AI-driven data analysis. The practical applicability and advantages of this technology are illustrated in the case study on noise-induced hearing loss (NIHL) in a foundry setting. By integrating environmental noise monitoring with individual health data, digital twins generate precise and personalized representations of the correlation between noise exposure and hearing health. This method improves the health and safety of workers by enhancing the accuracy and efficacy of risk assessments, resulting in more targeted and efficient interventions.

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