This study proposes the development of an AI-based smart desk-and-chair system designed to enhance students’ posture, health, and learning efficiency. In modern smart classrooms, physical environments are optimized, but poor posture still leads to health issues and reduced concentration. The proposed system uses AI technologies such as posture recognition via vision sensors and voice-controlled mode switching. The hardware includes motorized desk and chair adjustments, LED lighting, and a liftable bookshelf, all controlled by Arduino and Raspberry Pi. Each learning mode (focus, rest, reading, sleep) dynamically adjusts furniture position and lighting color temperature. A lightweight AI model enables real-time posture analysis, while voice commands trigger environment changes. The system is tested for accuracy, response speed, and usability. Results show posture recognition accuracy above 90%, confirming its effectiveness. This integrated solution contributes to personalized learning environments and promotes healthier study habits for students.

• 이희원(인하공업전문대학 기계설계공학과 재학생) | Hee-won Lee (Student, Dept. of Mechanical Design Engineering, Inha Technical College) Corresponding author
• 권서연(인하공업전문대학 기계설계공학과 재학생) | Seo-yeon Kwon (Student, Dept. of Mechanical Design Engineering, Inha Technical College) Corresponding author
• 이윤서(인하공업전문대학 기계설계공학과 재학생) | Yoon-seo Lee (Student, Dept. of Mechanical Design Engineering, Inha Technical College) Corresponding author
• 이정익(인하공업전문대학 기계설계공학과 교수) | Jeong-ick Lee