Research on an AI-Enabled Identification and Prevention 
System for the Mental Health of Vocational College Students

Guiping Dong; Qiang Fei; Xi Chen

doi:10.70711/aitr.v3i6.8596

Research on an AI-Enabled Identification and Prevention System for the Mental Health of Vocational College Students

Guiping Dong, Qiang Fei, Xi Chen

Abstract

Psychological problems among vocational college students have become increasingly prevalent, concealed, and complex. Traditional manual and experience-based intervention models suffer from limitations such as delayed identification, insufficient coverage, and low
precision. With the rapid advancement of artificial intelligence (AI) technologies, new technical pathways have emerged for mental health assessment and intervention. This study systematically explores the application of facial recognition, speech emotion analysis, natural language
processing, and behavioral feature mining to construct an intelligent mental health identification and prevention system. The proposed system
integrates multi-source data perception, intelligent analysis and decision-making, hierarchical intervention, and effectiveness evaluation,
aiming to realize proactive, precise, and continuous mental health management. This research provides both theoretical support and practical
guidance for the digital and intelligent transformation of mental health education in higher vocational colleges.

Keywords

Mental health; Artificial intelligence; Higher vocational colleges; Prevention and control system

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References

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DOI: http://dx.doi.org/10.70711/aitr.v3i6.8596

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