本論文是探討高齡長者的居家照顧服務架構，這實務上是一種的科技養老服務，應用科技與服務人員的結合，提供一種整體性的服務架構。本研究彙整了近20幾年客戶關係管理的發展及考慮大數據、智慧資訊、移動化與雲端化的科技應用，提出CRM iISA Model的完整服務架構，其內涵有三個要素一個支持，即互動、服務、分析三個要素及智慧一個支持，將企業運用客戶服務中心來服務廣大客戶的方法做提升，運用於居家照顧服務領域。
CRM iISA Model透過三個中心來形成完整的居家照顧服務架構。互動中心是提供全通路服務接入並納入物聯網感應器及各式機器人的應用，讓物聯網也成為服務管道之一。服務中心是將接入的服務需求提供最適切的服務流程，服務中心也具有流程客製化能力與管理能力，以滿足各種服務流程調整需求。分析中心能將服務歷程做分析，也將輿情、社群系統的間接管道納入，透過客戶之聲發現異常採取行動的機制，以滿足企業跟客戶的互動與服務需求。
CRM iISA Model應用於居家照顧領域，這養老方式特徵是被服務的居家長者是在家中，透過虛擬管道的觀察、通知、聯繫服務及部分面對面的現場居家服務來進行。在居家長者家中布建物聯網感應器，紀錄日常生活活動，也透過文字服務方式聯繫通知家屬，讓家屬能夠安心。服務中心提供居家長者的服務流程，也建立支持居服員、居服員督導、家屬的服務流程。居服員可以透過手機取得服務需求與紀錄服務狀況；居服員督導可以掌握服務品質與執行審核；家屬可獲得居家長者生活狀況或緊急通知。分析中心分析照護設施感應資料及各種服務資料，透過客戶之聲提供異常偵測與通知之功能，以此構成一個智慧化、行動化的居家照顧服務架構。
本研究主要貢獻是提出CRM iISA Model、標準化的物聯網感應器資料模型、資料分析的FLLST原則及居家長者日常活動行為辨識模型，這用以辨識居家長者行為，適時提供適當服務，這服務架構提供解決人口老化所面臨社會問題的一種解決方案。
Taiwan´s population is anxiously facing the problem of an aging population in a fast-paced manner, the rapid population aging society will face the need of taking care of the increased elderly population, increasing life assistance services demand, and creating a bigger burden on young people ... and other social problems. Living in this environment is a major trend in the future, and the establishment of a home care service system becomes very important.
This paper purpose is to explore the elderly care service framework for elderly people, this practice is a kind of technology pension service, application technology, and service personnel to provide a holistic service architecture. This study has compiled nearly 20 years of customer relationship management development and consider Big Data, Intelligent Information, Mobility and Cloud-based technology applications. It presents the complete service architecture of CRM iISA Model. Its connotation has three elements and one support. Intelligence to support elements of interaction, service and analysis. Use customer service centers to serve our customers enhancing the way to apply home care service in the area.
The CRM iISA Model forms a complete home care service architecture through three centers. The Interactive Center is to provide omnichannel service and the IoT sensors into various types of robot applications so that IoT technology becomes one of the service channel. The Service Center is to access the service needs to provide the most appropriate service process, the service center also has the process of customization and management capabilities to meet the needs of a variety of service processes adjustment needs. The Analysis Center can analyze the course of service, but also take the public opinion and social media, into the indirect service channel, through the Voice Of Customer service to find abnormal action mechanisms, to meet business, customer interaction and service needs.
The CRM iISA Model is applied in the field of home care, which serves the elderly at home, through the observation of virtual channel, notification, contact services and carried out part of the face-to-face home service to carry out. In the home of the elderly the deployment of IoT sensors, record activities of daily living, but also through the chat service to contact the family members, so that they can feel at ease. The service center provides the service process for the elderly and also establishes the service process for Nursing Aide service staff, Nursing Aide Supervisor, and family service process. The service staff can obtain the service demand and record service status through the mobile phone; the Nursing Aide Supervisor can master the service quality and the implement an audit review; the family member may have access to the living condition or the emergency notice of the living home. The analysis center analyzes the Home care IoT Device(HID) induction information and various service information, and through the voice of the customer provides abnormal detection and notification of the function, thus constituting the intelligent, mobility of home care service architecture.
This paper investigates and designs a set of data analysis methods for the data collected by the HID, proposes a Data Model, the FLLST principle of the HID data analysis and the ADL Behavior Recognizing Model (ABRM). The five principles of FLLST illustrate the basic logic of the analysis of HID and the limitations of processing, according to the development of the ABRM model, to identify the behavior of the elderly.
The main contribution of this study is to propose the CRM iISA Model, the standardized data model of the IoT sensors, data analysis of the FLLST principles and the ABRM of elderly, which is used to identify the behavior of the elderly and provide appropriate services in a timely manner. This service architecture provides a solution to address the social problems faced by population aging.