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.