Improvement of Student Weariness Emotion in English Classroom Based on Intelligent Internet of Things and Big Data Technology

In order to improve the recognition effect of student weariness emotion in English classroom, this paper combines intelligent Internet of Things technology and big data technology to construct an improvement model of student weariness emotion in English classroom. In the process of student facial ex...

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Bibliographic Details
Published in:Occupational therapy international 2022, Vol.2022, p.1-11
Main Author: Pang, Ya
Format: Article
Language:English
Subjects:
Academic achievement
Acknowledgment
Algorithms
Bias
Big Data
Child development
Children & youth
Classrooms
Cognition & reasoning
College students
Core curriculum
Education
Educational technology
Emotion recognition
Employment
Families & family life
Homework
Intelligence
Internet
Internet of Things
Learning
Mental health
Parents & parenting
Self evaluation
Students
Teaching methods
Technology
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Summary:In order to improve the recognition effect of student weariness emotion in English classroom, this paper combines intelligent Internet of Things technology and big data technology to construct an improvement model of student weariness emotion in English classroom. In the process of student facial expression recognition, according to the given grayscale threshold, this paper extracts the surface contour information from the three-dimensional volume data, extracts the student’s surface contour information, and uses triangular facets to fit to form a triangular mesh. Moreover, this paper renders a triangular mesh model and shows how to speed up the calculation of PFH. In addition, this paper proposes a Fast Point Feature Histogram, which uses an iterative closest point fine registration algorithm for image registration. Finally, this paper constructs an emotion recognition model of students’ weariness in English classroom. From the test results, it can be seen that the student weariness emotion recognition system in English classroom proposed in this paper can effectively identify students’ weariness emotion.
ISSN:0966-7903
1557-0703
DOI:10.1155/2022/9369389