Application of IoT Sensors and Data Analysis for the Early Detection of Physical and Chemical Hazards in Industrial Environments.

Abstract

Occupational safety and industrial hygiene are essential for protecting workers’ health and ensuring sustainable production processes. This article examines the application of Internet of Things (IoT) sensors and data analysis techniques for the early detection of physical and chemical risks in industrial environments. IoT systems enable continuous, real-time monitoring of critical environmental variables, such as noise, vibration, temperature, and chemical concentrations, overcoming the limitations of traditional point-measurement methods. Data analysis using statistical and predictive models allows for the identification of risk patterns, the generation of preventive alerts, and evidence-based decision-making. Integrating these technologies into occupational health and safety management systems, such as ISO 45001, promotes a proactive and continuous improvement approach, enhancing the prevention of accidents and occupational diseases. Implementation challenges, including costs, device interoperability, large-scale data management, and personnel training, are also discussed. Findings indicate that IoT sensors and data analysis constitute strategic tools that complement traditional methods, improving comprehensive worker protection and industrial risk management efficiency.