Advancing Research on Workers’ Fatigue in Construction: A Cluster-Based Review
Abstract
Workers’ fatigue research in the construction industry has advanced significantly with growing attention on the physical and mental aspects and their impacts on safety and health. As construction sites adopt more digital and sensor-based technologies, this study conducts a cluster-based review to highlight how fatigue detection has evolved into an advanced stage, featuring adaptive modeling, biochemical sensing, and artificial intelligence (AI)-driven prediction tools. Using VOSviewer bibliometric analysis, this review mapped the thematic structure of recent fatigue research and identified four key clusters: psychological health, cognitive-task performance, ergonomic and occupational risks, and physical health promotion. This cross-disciplinary approach merges physiological data analysis, AI, and construction ergonomics to provide practical insights for researchers and practitioners. Key recommendations include the need for large-scale field validation, multimodal sensor integration, and user-friendly wearable systems. Overall, this review consolidates current knowledge and outlines future directions to improve safety and resilience in construction environments.
Keywords: Construction workers’ fatigue, VOSviewer, AI-based safety systems
DOI: 10.54941/ahfe1006466
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