Optimization of the Music Teaching Management System Based on Emotion Recognition

Area of Science:

• Computer Science
• Educational Technology
• Music Education

Background:

• The increasing integration of computers in education necessitates robust teaching management systems.
• Effective information sharing and management are crucial for improving the quality of college education.
• Existing music teaching management systems may lack advanced features for personalized learning and efficient administration.

Purpose of the Study:

• To design and implement a practical music teaching management system software.
• To integrate Internet of Things (IoT) technology and emotion recognition into the system.
• To enhance information sharing, teaching quality, and overall college information construction.

Main Methods:

• System design based on the characteristics of music teaching and actual teaching situations.
• Incorporation of Internet of Things (IoT) technology and emotion recognition.
• Detailed description of subfunction module realization, hardware, and software implementation.
• Exploration of system structure analysis, database design, and data exchange.

Main Results:

• A comprehensive music teaching management system software design.
• Detailed implementation schemes for various system modules.
• Integration of IoT and emotion recognition for advanced functionality.
• A framework for practical music teaching management.

Conclusions:

• The developed system effectively addresses the needs of music teaching management.
• The integration of IoT and emotion recognition offers innovative solutions for educational technology.
• The system contributes to the advancement of college information construction in music education.