由於人口老齡化和出生率下降，以及雲服務的興起的趨勢。本研究提出支持分散式服務，運用事件驅動架構來建構具有分散式鬆偶合服務的老人居家服務。提出的模式可以建立可行的居家醫療互動服務模式，而且可以隨時照顧獨居老人的即時安全和健康管理。而相關的資訊傳遞是透過HL7 協定來進行存取，因此可以與其他相關的醫療資訊系統相互銜接，可以使醫護人員掌握老年人最新狀態與生理訊息，一旦發生緊急狀況時醫護人員可以給予最即時之協助，以輔助並保護其生命安全。
此外近年來，人口老齡化一直是被關注和重視的問題。隨著社會的發展逐漸進入老齡化社會，關愛老人人口已經成為一個至關重要的問題。因此，本文旨在建立有效的長期護理機構的人體感測網絡，以確保老年人口的移動安全和緊急監測，並進一步推動老人福利，以及提供醫療人員必要的資訊和協助。
本研究的重點是在運用人體感測網絡在醫療保健上，並經由感應器之間接收資訊，導入學習的概念與機制，用來實現後續相關處理及應用。在省電方面，因人體感測網路使用電池來供給電源。在本研究中提出了學習機制應用到節電的問題，它可有效達到相當程度的省電，對比正常狀況全速傳送時，省電幅度達到45%，故能達到長期有效監控之目的

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.

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