APPLYING THE DEEP LEARNING MODEL INTO THE FURNITURE PRODUCT DESIGN FOR THE ELDERLY

This paper aims to address the challenges posed by an aging society by leveraging deep learning and artificial intelligence (AI) technologies to enhance the quality of life for the elderly in smart city construction. This paper first explores the relationship between furniture design and the care and well-being of an aging society, proposing strategies for quality improvement. It then elaborates on the application of deep learning technology in furniture design, briefly introducing the algorithmic process. This paper specifically designs a convolutional neural network (CNN) model to analyze and evaluate the postures of the elderly, thereby supporting aging-friendly furniture design. Experimental results show that the recall value of the model reaches 0.9–1.0 in the training evaluation of four datasets, with precision values up to 96% and accuracy up to 98%. These results demonstrate that the model can effectively complete the posture assessment process for the elderly, providing crucial data support for intelligent furniture design. The contribution of this paper lies not only in providing technical support for the application of deep learning and AI technologies in future smart city construction but also in contributing to the sustainable development of social construction capabilities. The model is validated and improved through empirical research, ensuring its service of life design for the elderly, enhancing their quality of life and achieving a humanized and personalized intelligent home design. This, in turn, drives social progress. Future work will focus more on the practicality and adaptability of the model to better meet the safety and comfort needs of the elderly at home.