Journal of Applied Science and Engineering

Published by Tamkang University Press

ESCI jase impact factor scopus logo open access rate of Scopus journal

An AI-Enabled Smart Elderly Education Service Ecosystem from an Integrated Medical, Elderly Care, and Education Perspective

 2026

 Volume 33

Weina Guo1, Hui Xu1, Yuchao Xia2, and Le Yu3

1Hangzhou Polytechnic

2The College of Mathematics and Computer Science, Zhejiang A&F University

3The College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University

Received: March 16, 2026
Accepted: April 21, 2026
Publication Date: July 12, 2026

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Research framework of the AI-enabled smart elderly education service ecosystem. 

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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Population aging is accelerating worldwide, placing increasing pressure on healthcare systems and elderly care services. Although elderly education is recognized as an important component of active and healthy aging, existing services remain fragmented, with limited coordination among medical, care, and educational sectors. Meanwhile, advances in artificial intelligence (AI) offer new opportunities to support personalized and preventive interventions, yet their effective integration into elderly education and care remains insufficiently explored. This study proposes an AI-enabled smart elderly education service ecosystem from an integrated medical, elderly care, and education perspective. Drawing on service ecosystem theory and collaborative governance theory, the study conceptualizes medical services, elderly care, and education as interdependent subsystems and positions elderly education as a central intervention mechanism. A qualitative-oriented approach combining literature analysis and system modeling is adopted to design a layered architecture and an AI-centered operational mechanism. The results present an integrated service ecosystem supported by an AI middle platform that enables data fusion, personalized learning recommendations, and cross-domain coordination. Through mechanism-based analysis and scenario simulation, the proposed model demonstrates clear advantages over traditional fragmented approaches in terms of service integration, personalization, and preventive support. This study provides a conceptual framework and practical insights for developing sustainable and human-centered elderly education services in aging societies.

Keywords: Smart Elderly Education; Integrated Care; Service Ecosystem; Artificial Intelligence; Collaborative Governance

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