근로자의 건강관리 의사결정시스템 특허 트렌드 분석

Abstract

This study analyzed patent trends in decision support systems for worker health management to provide foundational data for future development of worker decision support systems. A total of 989 patents retrieved from the KIPRIS website, spanning from 1997 to 2025, were analyzed using Python-based Jupyter Notebook with keywords including "worker" and IPC codes (G16H/G06N/H04W). The analysis revealed four distinct periods of technological evolution: Period 1 exhibited a concentrated hub network centered on a few core technologies; Period 2 showed keyword diversification with the emergence of platform and smart technologies; Period 3 entered a convergent stage with the proliferation of AI and big data; and Period 4 demonstrated the convergence of mega-topics based on hyper-connected platforms and generative AI technologies, illustrating temporal changes across periods. Future research could verify whether shifts in network centrality correlate with actual industrial competitiveness, potentially serving as a strategic decision-making tool.