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IAServ: An Intelligent Home Care Web Services Platform in a Cloud for Aging-in-Place

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  • Chuan-Jun Su

    (Department of Industrial Engineering & Management, Yuan Ze University, No. 135, Yuan-Tung Rd., Chung-Li City, Taoyuan 320, Taiwan)

  • Chang-Yu Chiang

    (Department of Industrial Engineering & Management, Yuan Ze University, No. 135, Yuan-Tung Rd., Chung-Li City, Taoyuan 320, Taiwan)

Abstract

As the elderly population has been rapidly expanding and the core tax-paying population has been shrinking, the need for adequate elderly health and housing services continues to grow while the resources to provide such services are becoming increasingly scarce. Thus, increasing the efficiency of the delivery of healthcare services through the use of modern technology is a pressing issue. The seamless integration of such enabling technologies as ontology, intelligent agents, web services, and cloud computing is transforming healthcare from hospital-based treatments to home-based self-care and preventive care. A ubiquitous healthcare platform based on this technological integration, which synergizes service providers with patients’ needs to be developed to provide personalized healthcare services at the right time, in the right place, and the right manner. This paper presents the development and overall architecture of IAServ (the Intelligent Aging-in-place Home care Web Services Platform) to provide personalized healthcare service ubiquitously in a cloud computing setting to support the most desirable and cost-efficient method of care for the aged-aging in place. The IAServ is expected to offer intelligent, pervasive, accurate and contextually-aware personal care services. Architecturally the implemented IAServ leverages web services and cloud computing to provide economic, scalable, and robust healthcare services over the Internet.

Suggested Citation

  • Chuan-Jun Su & Chang-Yu Chiang, 2013. "IAServ: An Intelligent Home Care Web Services Platform in a Cloud for Aging-in-Place," IJERPH, MDPI, vol. 10(11), pages 1-25, November.
    • Handle: RePEc:gam:jijerp:v:10:y:2013:i:11:p:6106-6130:d:30354
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    References listed on IDEAS

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    1. Melanie Swan, 2009. "Emerging Patient-Driven Health Care Models: An Examination of Health Social Networks, Consumer Personalized Medicine and Quantified Self-Tracking," IJERPH, MDPI, vol. 6(2), pages 1-34, February.
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    1. Cristina Soguero-Ruiz & Inmaculada Mora-Jiménez & Javier Ramos-López & Teresa Quintanilla Fernández & Antonio García-García & Daniel Díez-Mazuela & Arcadi García-Alberola & José Luis Rojo-Álvarez, 2018. "An Interoperable System toward Cardiac Risk Stratification from ECG Monitoring," IJERPH, MDPI, vol. 15(3), pages 1-16, March.
    2. Yu-Feng Lin & Hsin-Han Shie & Yi-Ching Yang & Vincent S. Tseng, 2014. "Design of a Real-Time and Continua-Based Framework for Care Guideline Recommendations," IJERPH, MDPI, vol. 11(4), pages 1-18, April.
    3. Luciana Cardoso & Fernando Marins & Filipe Portela & Manuel Santos & António Abelha & José Machado, 2014. "The Next Generation of Interoperability Agents in Healthcare," IJERPH, MDPI, vol. 11(5), pages 1-23, May.
    4. Katrien Luijkx & Sebastiaan Peek & Eveline Wouters, 2015. "“Grandma, You Should Do It—It’s Cool” Older Adults and the Role of Family Members in Their Acceptance of Technology," IJERPH, MDPI, vol. 12(12), pages 1-16, December.
    5. Tuochen Li & Siran Wang, 2021. "How to Improve the Public Trust of the Intelligent Aging Community: An Empirical Study Based on the ACSI Model," IJERPH, MDPI, vol. 18(4), pages 1-14, February.

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