Embedded Psychological Health Monitoring and Psychological Quality Management for Vocational College Students Based on Cloud Integration

This paper utilizes mobile cloud integration based on healthcare embedded systems to implement personalized intervention measures, in order to enhance the effectiveness of students’ mental health and overall quality. This study conducted comprehensive and systematic psychological health monitoring and psychological quality assessment through a mobile cloud-integrated SI platform based on healthcare embedded systems. With the help of advanced clustering analysis algorithms, the platform can accurately identify the psychological characteristics of different student groups and design highly personalized intervention plans based on this. The experimental results showed that after implementing personalized intervention, there were significant improvements in students’ mental health status, comprehensive quality, academic performance, and interpersonal relationships. Especially the improvement of emotional management ability, teamwork ability, and innovative thinking ability has laid a solid foundation for students’ future career development. This study not only provides a new perspective and method for student management in vocational colleges but also provides a useful reference and inspiration for promoting the application of mobile cloud integration technology for healthcare embedded systems in the field of education, especially in psychological health monitoring and psychological quality management.

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Publication Details

Journal
International Journal of High Speed Electronics and Systems
Published
2025-06-24
DOI
https://doi.org/10.1142/s0129156425406448
Primary Topic
Advanced Technologies in Various Fields
Type
article
Field-Weighted Citation Impact
0.00
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article

Embedded Psychological Health Monitoring and Psychological Quality Management for Vocational College Students Based on Cloud Integration

Li Huichao, Sun Quanzhen
International Journal of High Speed Electronics and Systems
Advanced Technologies in Various Fields
article

Embedded Psychological Health Monitoring and Psychological Quality Management for Vocational College Students Based on Cloud Integration

Li Huichao, Sun Quanzhen
article en

Abstract

This paper utilizes mobile cloud integration based on healthcare embedded systems to implement personalized intervention measures, in order to enhance the effectiveness of students’ mental health and overall quality. This study conducted comprehensive and systematic psychological health monitoring and psychological quality assessment through a mobile cloud-integrated SI platform based on healthcare embedded systems. With the help of advanced clustering analysis algorithms, the platform can accurately identify the psychological characteristics of different student groups and design highly personalized intervention plans based on this. The experimental results showed that after implementing personalized intervention, there were significant improvements in students’ mental health status, comprehensive quality, academic performance, and interpersonal relationships. Especially the improvement of emotional management ability, teamwork ability, and innovative thinking ability has laid a solid foundation for students’ future career development. This study not only provides a new perspective and method for student management in vocational colleges but also provides a useful reference and inspiration for promoting the application of mobile cloud integration technology for healthcare embedded systems in the field of education, especially in psychological health monitoring and psychological quality management.

International Journal of High Speed Electronics and Systems
Openalex Percentile: Top 93%
Advanced Technologies in Various Fields
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Embedded Psychological Health Monitoring and Psychological Quality Management for Vocational College Students Based on Cloud Integration — Li Huichao, Sun Quanzhen · International Journal of High Speed Electronics and Systems (2025) | TGRS Research Map | TGRS