In recent years, work environments have witnessed a significant transformation in mechanisms for maintaining employee health and safety, driven by rapid advancements in sensing technologies, the Internet of Things, and data analytics. Occupational safety procedures are no longer limited to traditional instructions or periodic medical examinations; instead, they increasingly rely on intelligent systems capable of continuous monitoring and immediate response to potential risks. This transformation aligns with the global direction represented by the Sustainable Development Goals adopted by the United Nations, particularly Goal 3, which focuses on good health and well-being. Wearable devices play a pivotal role in this context, as they enable real-time collection of physiological and environmental data while employees perform their duties. These devices include smartwatches, sensor-equipped wristbands, smart helmets, and intelligent garments capable of measuring vital indicators such as heart rate, body temperature, blood oxygen levels, as well as monitoring physical strain and exposure to hazardous gases or high temperatures. The collected data are transmitted to centralized analytical platforms that detect abnormal changes which may indicate imminent health risks, allowing for early intervention before conditions worsen. The importance of these technologies is particularly evident in high-risk sectors such as heavy industries, mining, construction, and healthcare. For instance, sensor-based systems can detect signs of fatigue or heat stress among workers in hot environments and automatically issue alerts recommending rest breaks, thereby reducing accidents caused by exhaustion or loss of concentration. Additionally, movement tracking technologies can analyze repetitive motions and improper body postures to prevent musculoskeletal injuries, which are among the most common occupational health issues. Alongside wearable technologies, information technology systems play a complementary role in strengthening occupational health and safety frameworks. Digital health and safety management systems allow for documentation of incidents, root cause analysis, and identification of recurring patterns to develop effective preventive strategies. Moreover, big data analytics and machine learning techniques enable organizations to predict high-risk zones or time periods with increased accident probability, based on historical and real-time data. These technological systems also contribute to improving overall working conditions by supporting data-driven decision-making. Management can assess the impact of long working hours, workload pressure, and workforce distribution on employee health, thereby adjusting policies to enhance the balance between productivity and employee well-being. Digital platforms further facilitate interactive safety training programs, equipping workers with effective emergency response skills. Despite these advantages, the adoption of health monitoring technologies raises important concerns regarding data privacy and security. The collection of employees’ health data requires clear legal and regulatory frameworks to ensure ethical use and prevent misuse. Therefore, successful implementation depends on achieving a careful balance between safeguarding employee health and respecting individual privacy, while fostering transparency and trust between employers and staff. Overall, technology represents a strategic tool for transforming occupational health systems from a reactive model, which responds after incidents occur, to a proactive model focused on prediction and prevention. Through the intelligent integration of wearable devices and advanced information systems, safer, healthier, and more sustainable work environments can be established, generating positive impacts for individuals, institutions, and society. Al-Mustaqbal University – The First University in Iraq.