基于智慧物联网的社区老年健康监测服务设计研究

目的 全球老龄化对医疗保健系统造成了冲击，给老年群体的医护服务供需平衡带来了重大挑战，为提高就医便捷性、促进健康问题早期发现，以及预防性医护服务的定制化、系统化，探讨了一种创新的智慧社区老年医护服务模式。方法 基于物联网(IoT)技术和人工智能(AI)算法，构建了以传感器多路采集为数据来源的物联网健康监测框架，开发了融合传感器、电子医疗记录和病例样本数据为特征数据的机器学习疾病预测模型，并在此基础上设计了远程医护服务平台应用程序，构成了智慧社区老年健康监测服务模式。结论 系统以物联网-人工智能-交互终端为核心，利用老年人生理数据预测其慢性病风险进而实现提前预警，便于提供及时的干预措施，为医患双方提供沟通媒介及辅助诊断工具。系统有望推动养老医护服务的发展，提高服务的可及性与有效性。

Design of Community Elderly Health Monitoring Service Based on Smart Internet of Things

Global aging has impacted the healthcare system, posing significant challenges to the supply and demand balance of medical services for the elderly. In order to promote the development of elderly healthcare services in the context of aging and digital intelligence, and improve the effectiveness and accessibility of services, the work aims to explore an innovative smart community elderly healthcare service model. Based on the Internet of Things (IoT) technology and artificial intelligence (AI) algorithms, an IoT health monitoring framework was constructed with sensor multi-channel collection as the data source. A disease prediction model through machine learning was developed, incorporating sensors, electronic medical records, and case sample data as feature data. On this basis, a remote medical service platform application was designed, forming a smart community elderly health monitoring service model. The system is centered around the Internet of Things, artificial intelligence, and interactive terminals, utilizing physiological data of the elderly to predict their chronic disease risks and achieve early warning, facilitating timely intervention measures, and providing communication media and auxiliary diagnostic tools for both doctors and patients. It is expected to promote the development of elderly medical services and improve the effectiveness and accessibility of services.