Machine Learning Based Academic Stress Management System

被引:5
|
作者
Thanasekhar, B. [1 ]
Gomathy, N. [1 ]
Kiruthika, A. [1 ]
Swarnalaxmi, S. [1 ]
机构
[1] Anna Univ, Dept Comp Technol, MIT Campus, Chennai, Tamil Nadu, India
来源
2019 11TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING (ICOAC 2019) | 2019年
关键词
stress; machine learning; academic stress; activity based stress; students;
D O I
10.1109/ICoAC48765.2019.246831
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Living with stress has become a part of our lifestyle. Stress is directly linked to cause long-term health problems [1]. Students are no exceptions; they undergo stress and strains in facing new situations, where the outcome is uncertain. Their academic performance is challenged by problems and managing time. Due to overwhelming problems they cannot Figure out their stress causing factors. As it is not possible for a physician to continuously monitor stress levels and diagnose it[5], this proposal deals with identifying the level of stress using wearable bio-sensors and providing constructive actions to be taken to overcome it effectively. We use intelligent Machine learning models to monitor students' lifestyle. The outcome can be used to identify an ideal student who can portray as a role model in improving the academic growth of a student. An ideal student is the one who manages stress as well as obtains good grades in academics.
引用
收藏
页码:147 / 151
页数:5
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