Development of a Remote Social Work Service Platform Integrating 5G Network and IoT Technology

This research endeavors to create a remote long-term care social work service platform that incorporates fifth-generation mobile communication (5G) and Internet of Things (IoT) technologies, aiming to address the limitations of conventional service models in the context of an aging population. The study utilizes a mixed-methods approach, conducting pilot tests of the platform across four urban and rural long-term care facilities in Taiwan. The findings demonstrate that the platform effectively leverages the low latency and high bandwidth capabilities of 5G in conjunction with IoT sensor networks, resulting in a marked enhancement in service efficiency. Quantitative analyses reveal significant improvements in service satisfaction, social workers’ professional self-efficacy, and the accessibility of services in remote regions following the platform’s implementation. Qualitative assessments indicate that while the new service model offers increased convenience and reassurance, it also introduces challenges, including the digital divide among elderly users, concerns regarding privacy, and the need for adaptation in professional roles. In conclusion, the study affirms that the integration of 5G and IoT technologies presents substantial technical feasibility and practical value, effectively fostering service innovation and quality enhancement. Nevertheless, the successful deployment of such technology necessitates a comprehensive digital empowerment initiative, robust privacy protection frameworks, and ethical guidelines to strike a balance between technological advancement and humanistic care, thereby facilitating the realization of sustainable and inclusive smart care services.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-30
DOI
https://doi.org/10.5281/zenodo.16600688
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Development of a Remote Social Work Service Platform Integrating 5G Network and IoT Technology

Zenodo (CERN European Organization for Nuclear Research)
Context-Aware Activity Recognition Systems
article

Development of a Remote Social Work Service Platform Integrating 5G Network and IoT Technology

article en

Abstract

This research endeavors to create a remote long-term care social work service platform that incorporates fifth-generation mobile communication (5G) and Internet of Things (IoT) technologies, aiming to address the limitations of conventional service models in the context of an aging population. The study utilizes a mixed-methods approach, conducting pilot tests of the platform across four urban and rural long-term care facilities in Taiwan. The findings demonstrate that the platform effectively leverages the low latency and high bandwidth capabilities of 5G in conjunction with IoT sensor networks, resulting in a marked enhancement in service efficiency. Quantitative analyses reveal significant improvements in service satisfaction, social workers’ professional self-efficacy, and the accessibility of services in remote regions following the platform’s implementation. Qualitative assessments indicate that while the new service model offers increased convenience and reassurance, it also introduces challenges, including the digital divide among elderly users, concerns regarding privacy, and the need for adaptation in professional roles. In conclusion, the study affirms that the integration of 5G and IoT technologies presents substantial technical feasibility and practical value, effectively fostering service innovation and quality enhancement. Nevertheless, the successful deployment of such technology necessitates a comprehensive digital empowerment initiative, robust privacy protection frameworks, and ethical guidelines to strike a balance between technological advancement and humanistic care, thereby facilitating the realization of sustainable and inclusive smart care services.

Zenodo (CERN European Organization for Nuclear Research)
Chang Jung Christian University (TW)
Industry, innovation and infrastructure
Openalex Percentile: Top 52%
Context-Aware Activity Recognition Systems
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