Human-Centricity in Industry 5.0: A Survey of Worker Sensing, Adaptive Operations, and Human-in-the-Loop Systems

Abstract

Industry 5.0 (I5.0) repositions manufacturing around a human-centric vision in which cyber-physical systems must adapt to the worker rather than the other way around. Despite significant advances in worker state monitoring technologies, including markerless computer vision, wearable physiological sensors, and machine-learning-based fatigue and cognitive load estimation, a critical integration gap persists: these monitoring capabilities rarely inform real-time operational decisions, and workers almost never participate in the adaptive processes that affect their tasks and workloads. This paper presents a structured survey of the state-of-the-art across three interconnected dimensions: (1) worker state monitoring in industrial settings, encompassing physical fatigue, cognitive load, and ergonomic risk assessment; (2) human factors integration in Operations Management (OM) models, examining how scheduling, task allocation, and production planning incorporate worker-related objectives; and (3) Human-in-the-Loop (HITL) architectures, analyzing the extent to which worker feedback closes the adaptive decision loop. The survey reveals that while each dimension has matured independently, the integration across them remains largely absent. Based on the reviewed literature, no publicly documented and validated system connects real-time sensor-driven worker state estimation with adaptive OM decisions and worker feedback in a unified closed-loop architecture. This gap is identified as the central challenge for realizing the I5.0 vision, and a five-direction research agenda is proposed.