Purpose/Significance To uncover the hot topics of research in the field of smart elderly care in China. Method/Processe CNKI is selected as the search database, and the abstracts of journal papers, dissertations and conference papers in the field of smart elderly care from 2004 to 2023 are used as the research data. Text mining is carried out with the help of the LDA topic model, combining the perplexity degree with the consistency to determine the optimal number of topics in the model. Topic identification is performed based on topic-term distribution, and topic intensity is calculated based on document-topic distribution. Result/Conclusion A total of 9 topics in the field of smart elderly care in China are extracted through the LDA topic model, among which the hot topics are service architecture, digital transformation, community elderly care, and user research.