With the development of digital information technology, digital products have been integrated into people's lives. The advent of the era of big data and the application of artificial intelligence have greatly accelerated this process. However, the increasingly high-end technology of these digital products brings more and more complex operations. The use and operation of these digital products have become a huge problem for the elderly who have a low level of acceptance of digital products or even a little out of touch. The purpose of this article is to study the influence of synesthetic design of digital senior products based on big data on the development of digital senior products. This article first understands the current problems in the development of digital elderly products and the design concepts and design processes of these digital elderly products through questionnaire surveys and market research. Then, this article analyzes the importance of synesthesia design for digital product design for the elderly through literature research and related product design cases. Then, this article combines the application of big data technology and complex intelligent system to carry out the synesthesia design of digital elderly products, the most important of which is to use the image recognition technology of complex intelligent system and intelligent voice interaction technology to achieve the synesthesia effect of these product designs. Finally, this paper uses the mathematical model of maximum utility and some statistical methods to analyze the effect of the product synesthesia design experiment in this research. Studies have shown that synesthesia design can maximize the utility of digital products for the elderly. This result is more than 95% confident in statistical analysis. Therefore, synesthesia design plays an important role in the popularization and development of digital elderly products in the elderly consumer groups.
CITATION STYLE
Li, S. (2021). Synesthetic Design of Digital Elderly Products Based on Big Data. Wireless Communications and Mobile Computing, 2021. https://doi.org/10.1155/2021/5596571
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