Industry 4.0 technologies, including artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), cloud computing, and digital twin (DT) simulations, are being explored for safety evaluation and exposure assessment in industrial environments. These technologies offer innovative solutions for accident prevention, risk mitigation, and the monitoring of airborne hazards. Smart sensors, wearable devices, and virtual and augmented reality (VR/AR) platforms support employee training, real-time hazard detection, and the development of safety strategies. However, challenges such as employee stress, cybersecurity, data handling, and privacy concerns remain. Future research should focus on the ethical, policy, and regulatory aspects of these technologies. Airborne hazards, including particulate matter (PM), volatile organic compounds (VOC), and bioaerosols, pose significant health risks in occupational settings. PM, especially ultrafine particles (UFPs), can penetrate deep into the respiratory system, causing inflammation and oxidative stress. Bioaerosols, such as bacteria, fungi, and viruses, can lead to respiratory diseases and hypersensitivity pneumonitis. Exposure to welding fumes, spray paint, and other industrial chemicals can result in respiratory issues, lung cancer, and other health problems. Industry 4.0 tools, such as IoT, cloud computing, and DT, enable real-time data exchange, predictive analytics, and simulation for hazard monitoring and control. These technologies support the development of smart personal protective equipment (PPE), ergonomic work environments, and automated systems that reduce human exposure to hazards. However, the integration of these technologies requires careful consideration of ethical, regulatory, and technical challenges. Exposure assessment tools, including AI algorithms, real-time sensors, and digital twins, are being developed to improve the accuracy of hazard detection and risk mitigation. These tools can predict airborne pollutant concentrations, monitor indoor air quality, and support the design of effective safety measures. However, the effectiveness of these tools depends on data quality, sensor validation, and the integration of multiple technologies. Despite the potential benefits of Industry 4.0 technologies, challenges such as data security, ethical concerns, and the need for regulatory frameworks must be addressed to ensure their safe and effective implementation in industrial environments. Future research should focus on refining these technologies, improving data management, and developing policies that support the ethical and sustainable use of Industry 4.0 in occupational safety and exposure assessment.Industry 4.0 technologies, including artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), cloud computing, and digital twin (DT) simulations, are being explored for safety evaluation and exposure assessment in industrial environments. These technologies offer innovative solutions for accident prevention, risk mitigation, and the monitoring of airborne hazards. Smart sensors, wearable devices, and virtual and augmented reality (VR/AR) platforms support employee training, real-time hazard detection, and the development of safety strategies. However, challenges such as employee stress, cybersecurity, data handling, and privacy concerns remain. Future research should focus on the ethical, policy, and regulatory aspects of these technologies. Airborne hazards, including particulate matter (PM), volatile organic compounds (VOC), and bioaerosols, pose significant health risks in occupational settings. PM, especially ultrafine particles (UFPs), can penetrate deep into the respiratory system, causing inflammation and oxidative stress. Bioaerosols, such as bacteria, fungi, and viruses, can lead to respiratory diseases and hypersensitivity pneumonitis. Exposure to welding fumes, spray paint, and other industrial chemicals can result in respiratory issues, lung cancer, and other health problems. Industry 4.0 tools, such as IoT, cloud computing, and DT, enable real-time data exchange, predictive analytics, and simulation for hazard monitoring and control. These technologies support the development of smart personal protective equipment (PPE), ergonomic work environments, and automated systems that reduce human exposure to hazards. However, the integration of these technologies requires careful consideration of ethical, regulatory, and technical challenges. Exposure assessment tools, including AI algorithms, real-time sensors, and digital twins, are being developed to improve the accuracy of hazard detection and risk mitigation. These tools can predict airborne pollutant concentrations, monitor indoor air quality, and support the design of effective safety measures. However, the effectiveness of these tools depends on data quality, sensor validation, and the integration of multiple technologies. Despite the potential benefits of Industry 4.0 technologies, challenges such as data security, ethical concerns, and the need for regulatory frameworks must be addressed to ensure their safe and effective implementation in industrial environments. Future research should focus on refining these technologies, improving data management, and developing policies that support the ethical and sustainable use of Industry 4.0 in occupational safety and exposure assessment.