An Intelligent Handwriting and Painting Teaching System Based on Artificial Intelligence Edge Computing Technology

In this article, a handwriting teaching system based on artificial intelligence (AI) edge computing technology is proposed. The proposed system combines gesture tracking, gesture recognition, and other related AI technologies. Additionally, the development platform for AI edge computing in this system is developed to teach handwriting and practice drawing. The proposed system is composed of a teacher-end teaching host and several student-end AI edge computing smart devices. The student-end AI edge computing smart device incorporates virtual drawing and writing, finger digital computing teaching, a virtual keyboard, virtual sliding, and sleep prevention warnings. The teacher-end teaching host allows the teacher to conduct a teaching course. Moreover, the teacher-end teaching host and the student smart device can simultaneously display images on a large screen to facilitate teaching demonstrations. Furthermore, this system has a comprehensive data storage cloud platform, which can record the data uploaded by each student to a storage cloud platform to facilitate teaching evaluations. This work differs from traditional handwriting and painting technique studies in the classroom, and the AI virtual drawing technology proposed in this work can produce impressive visual effects for visual media, including animation, graphics, and text.

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Publication Details

Journal
Canadian Journal of Electrical and Computer Engineering
Published
2025-01-01
DOI
https://doi.org/10.1109/icjece.2025.3550383
Primary Topic
Digital Media and Visual Art
Type
article
Field-Weighted Citation Impact
0.00
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article

An Intelligent Handwriting and Painting Teaching System Based on Artificial Intelligence Edge Computing Technology

Liang-Bi Chen, Xiang-Rui Huang, Hsin-Yu Chen
Canadian Journal of Electrical and Computer Engineering
Digital Media and Visual Art
article

An Intelligent Handwriting and Painting Teaching System Based on Artificial Intelligence Edge Computing Technology

Liang-Bi Chen, Xiang-Rui Huang, Hsin-Yu Chen
article en

Abstract

In this article, a handwriting teaching system based on artificial intelligence (AI) edge computing technology is proposed. The proposed system combines gesture tracking, gesture recognition, and other related AI technologies. Additionally, the development platform for AI edge computing in this system is developed to teach handwriting and practice drawing. The proposed system is composed of a teacher-end teaching host and several student-end AI edge computing smart devices. The student-end AI edge computing smart device incorporates virtual drawing and writing, finger digital computing teaching, a virtual keyboard, virtual sliding, and sleep prevention warnings. The teacher-end teaching host allows the teacher to conduct a teaching course. Moreover, the teacher-end teaching host and the student smart device can simultaneously display images on a large screen to facilitate teaching demonstrations. Furthermore, this system has a comprehensive data storage cloud platform, which can record the data uploaded by each student to a storage cloud platform to facilitate teaching evaluations. This work differs from traditional handwriting and painting technique studies in the classroom, and the AI virtual drawing technology proposed in this work can produce impressive visual effects for visual media, including animation, graphics, and text.

Canadian Journal of Electrical and Computer EngineeringVol. 48(2)
National Penghu University of Science and Technology (TW)
Quality Education
Openalex Percentile: Top 87%
Digital Media and Visual Art
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