Smart Elderly Healthcare Services in Industry 5.0: A Survey of Key Enabling Technologies and Future Trends
This survey presents a comprehensive analysis of the transformative role of Industry 5.0 technologies in advancing smart elderly healthcare services, focusing on China’s evolving digital landscape. By examining the opportunities and challenges unique to China’s aging population in the context of rapid technological integration, the study outlines a system architecture that underpins next-generation elderly healthcare ecosystems. Central to this framework are five pivotal enabling technologies: the Internet of Things (IoT), Edge Computing, Service Robots, Big Data Analytics, and Digital Twin, each systematically explored to highlight their contributions to personalized, proactive, and decentralized elderly healthcare. The survey identifies critical application challenges, including interoperability gaps, ethical concerns in human-robot interaction, and data heterogeneity, while forecasting future trends poised to accelerate the adoption of Industry 5.0 principles. Emerging directions such as context-aware robotic collaboration, federated learning for privacy-preserving analytics, and metaverse-integrated digital twins are underscored as catalysts for sustainable, human-centric solutions. By bridging technological innovation with socio-ethical considerations, this work not only maps current advancements but also advocates for a paradigm shift toward empathetic, adaptive, and equitable elderly healthcare systems. The findings aim to inspire interdisciplinary collaboration among researchers, policymakers, and healthcare providers, fostering a transition to intelligent, dignity-preserving care models that align with the human-centered ethos of Industry 5.0.
Authors
- Dongni Wang (ORCID: https://orcid.org/0000-0002-7130-6408)
- Li Xia Huang (ORCID: https://orcid.org/0000-0002-2478-5565)
- Peng Guo (ORCID: https://orcid.org/0000-0001-5520-7701)
- Xiaoling Wang (ORCID: https://orcid.org/0000-0003-2136-7410)
- Liangliang Liu (ORCID: https://orcid.org/0000-0003-3405-355X)
Institutions
- Panzhihua University (CN)
- Southwest Jiaotong University (CN)
Publication Details
- Journal
- IEEE Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/access.2025.3596694
- Citations
- 1
- Primary Topic
- Impact of AI and Big Data on Business and Society
- Type
- article
- Field-Weighted Citation Impact
- 2.11