Embedded Intelligent Elderly Care System Based on Deep Learning

DOI: https://doi.org/10.62517/jmhs.202305112

Author(s)

Yun Lu1, Saiwen Li2,*

Affiliation(s)

1School of Mechatronics and Automation, Wuchang Shouyi University, Wuhan, Hubei 430064, China 2Schoool of Journalism and Communications, Wuhan University of Communication, Wuhan, Hubei 430064, China *Corresponding Author

Abstract

At present, the elderly care service industry has the problems of low information integration and low data utilization. To solve the above problems, building an embedded pension service platform is one of the most effective means. This paper constructs an embedded pension service model based on deep learning. In this paper, a multi-objective optimization recommendation algorithm based on artificial immune is used to generate service recommendation candidate sets. Develop an embedded personalized elderly care service platform according to the candidate set. This paper makes a detailed demand analysis and functional module design of the elderly service recommendation system, and finally designs and implements the embedded elderly service system. The experimental results show that compared with the user based collaborative filtering algorithm and the improved collaborative filtering, the highest accuracy of this method is improved by 0.09 and 0.07 respectively, and the highest service satisfaction is improved by 2.05 and 2.4 respectively. This method has certain reference value for the research of embedded intelligent elderly care system based on deep learning.

Keywords

Pension Service; Embedded Model; Multi-Objective Optimization Recommendation Algorithm; Data Fusion

References

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