Integrating Wearable AI Technology for Construction Worker Safety

The construction industry remains among the most hazardous occupational sectors, with persistently high rates of injury and fatality. Traditional safety measures—although widely adopted—often function reactively and fail to anticipate dynamic on-site risks. This paper investigates the role of artificial intelligence (AI)-enabled wearable technologies, including smart helmets, biometric vests, exoskeletons, and fatigue detection systems, in transforming safety practices through real-time monitoring and predictive analytics. These innovations enable continuous assessment of workers' health parameters, early detection of fatigue, and automated safety interventions, thereby facilitating a shift from passive to proactive risk management. Despite their transformative potential, significant barriers, such as ethical concerns regarding biometric data, integration challenges, and high implementation costs, hinder widespread adoption. This paper advocates for further research on enhancing technical reliability, regulatory frameworks, and cost-effectiveness to foster scalable deployment of AI wearables in construction environments.