An Event-based Architecture for Cloud Elderly Home-care Service Model

博士 === 國立成功大學 === 工程科學系 === 103 === To address of the trend of population aging and declining birth rates, as well as the emergence of cloud services, this study proposed an event-driven architecture-based model to support collaborative distributed services. The proposed model can accommodate lo...

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Bibliographic Details
Main Authors: Chyun-ChyiChen, 陳群奇
Other Authors: Yueh-Min Huang
Format: Others
Language:en_US
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/52766239389612973468
Description
Summary:博士 === 國立成功大學 === 工程科學系 === 103 === To address of the trend of population aging and declining birth rates, as well as the emergence of cloud services, this study proposed an event-driven architecture-based model to support collaborative distributed services. The proposed model can accommodate loosely coupled distributed services aimed at providing home care services for elderly adults who live alone through the development of an interactive home care service model; thus, the proposed model facilitates providing immediate safety and health management. The event messages of the proposed system architecture were based on the Health Level 7 (HL7) protocol. Thus, the system can provide rapid support for medical treatment and is compatible with all HL7-based medical information systems, thus enabling medical staff to provide immediate assistance to elderly adults in the event of an emergency. In recent years, population aging has been an ongoing concern. As societies gradually transition to an aging society, providing care for the elderly population becomes a crucial issue. Therefore, this paper also presents a mechanism for providing long-term care through a body sensor network (BSN) to ensure the mobile security and emergency monitoring of elderly adults. Moreover, the proposed mechanism can further facilitate providing welfare services for elderly adults as well as necessary information and assistance for medical personnel. This study focused on investigating health care by analyzing BSN data. The concept and learning mechanism are introduced to demonstrate how the proposed system can fulfill follow-up processing and applications. Moreover, because the BSN is powered by batteries, it effectively uses 45% less power than full-speed transmission networks operating under normal conditions. Thus, effective long-term monitoring is demonstrated in this paper.