IoT-driven Framework for Enhancing Human Resource Management System in Digital Era

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Authors: Ce Shi, Mohd Anuar Bin Arshad, Jiangwei Luo, Cheng-Fu Yang
Cited by: 0

Abstract

In the current era of digital transformation, enterprises are increasingly reliant on intellectual capital and collaborative efficiency.Traditional human resource management systems (HRMSs) are facing significant challenges in adapting to these evolving demands.The advent of IoT presents promising opportunities for the enhancement of HRMS functionalities.While IoT technologies have been widely applied in industrial manufacturing, their systematic integration into the domain of HRM remains underexplored.In this study, we provide a comprehensive analysis of the potential benefits and challenges associated with IoT adoption in HRMSs.We propose an optimized framework grounded in a four-layer IoT architecture, incorporating sensing devices, blockchain, and AI technologies.The framework highlights sensor-based data acquisition as a fundamental enabler for real-time, human-centric information sensing in HRMSs.The proposed model addresses critical issues such as employee interaction, knowledge integration, and data privacy, with the goal of improving the real-time responsiveness and accuracy of HR operations.Although in this study we focus on framework design rather than experimental implementation, the proposed architecture is built on mature IoT and sensing technologies, suggesting practical feasibility in real organizational settings.By presenting a cohesive architecture, we offer practical insights for HRMS practitioners, system implementers, and technology developers.Moreover, in this study, we will serve as a reference for deploying IoT technologies within complex organizational ecosystems.This work is relevant to readers interested in sensing concepts, as it extends sensor-enabled systems from physical environments to organizational and human-centered applications.The main limitation of this study lies in the lack of empirical validation through prototype deployment.Future work will focus on system implementation and experimental evaluation to further verify applicability and performance.Ultimately, this work aims to foster innovation in HRMSs and strengthen the digital capabilities of modern enterprises.

Fields of Study & Subjects

AI and HR Technologies Internet of Things and AI IoT and Edge/Fog Computing

Publication details

Journal / source
Sensors and Materials
Volume
38
Issue
1
Pages
405–405
Publication date
28 January 2026
Language
EN