Integrating Wireless Passive Sensor Technology Into Smart Manufacturing Education: A Teaching Framework From Theory to Practice

ABSTRACT With the rapid development of intelligent manufacturing, it is imperative that the engineering education system urgently needs to evolve in sync with cutting‐edge industrial technologies. The industrial sector has widely adopted advanced technologies such as wireless passive sensors (WPS), but the content of relevant courses in universities still lags behind technological development, especially in the integration of new sensing mechanisms such as WPS into mechatronics and sensor courses, which have obvious shortcomings. To fill this gap, a comprehensive teaching framework that integrates “Theory, Design, Preparation, Testing” was proposed in this article. This framework integrates the basic theory of microwave sensing, electromagnetic simulation practice, intelligent optimization design based on transformer neural network, convenient digital manufacturing methods, and actual sensing testing, aiming to help students systematically master the full process capability of WPS from theory to practice through a layered and progressive teaching path. The introduction of encoding structures and neural network prediction methods significantly improves the efficiency and effectiveness of sensor performance optimization, enabling students to experience a paradigm shift from traditional empirical design to data‐driven intelligent design. At the same time, by replacing traditional MEMS processes with 3D printing technology, the complexity, costness, and difficulties to implement micro‐nano processing equipment have been effectively solved, achieving rapid closed‐loop verification from concept to physical object. The effectiveness of this framework has been verified through multi‐dimensional student feedback. The framework not only cultivates students' interdisciplinary integration abilities in the fields of digital manufacturing and industrial IoT, but also provides an extensible teaching practice path for engineering education to adapt to technological development.

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Publication Details

Journal
Computer Applications in Engineering Education
Published
2026-05-01
DOI
https://doi.org/10.1002/cae.70195
Primary Topic
Nanotechnology research and applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Integrating Wireless Passive Sensor Technology Into Smart Manufacturing Education: A Teaching Framework From Theory to Practice

Yang Gao, J F Zhang, Kaihao Liang, Fuzhen Xuan et al.
Computer Applications in Engineering Education
Nanotechnology research and applications
article

Integrating Wireless Passive Sensor Technology Into Smart Manufacturing Education: A Teaching Framework From Theory to Practice

Yang Gao, J F Zhang, Kaihao Liang, Fuzhen Xuan, Huating Tu, Shunzhen Tao, Yang Zhang
article en

Abstract

ABSTRACT With the rapid development of intelligent manufacturing, it is imperative that the engineering education system urgently needs to evolve in sync with cutting‐edge industrial technologies. The industrial sector has widely adopted advanced technologies such as wireless passive sensors (WPS), but the content of relevant courses in universities still lags behind technological development, especially in the integration of new sensing mechanisms such as WPS into mechatronics and sensor courses, which have obvious shortcomings. To fill this gap, a comprehensive teaching framework that integrates “Theory, Design, Preparation, Testing” was proposed in this article. This framework integrates the basic theory of microwave sensing, electromagnetic simulation practice, intelligent optimization design based on transformer neural network, convenient digital manufacturing methods, and actual sensing testing, aiming to help students systematically master the full process capability of WPS from theory to practice through a layered and progressive teaching path. The introduction of encoding structures and neural network prediction methods significantly improves the efficiency and effectiveness of sensor performance optimization, enabling students to experience a paradigm shift from traditional empirical design to data‐driven intelligent design. At the same time, by replacing traditional MEMS processes with 3D printing technology, the complexity, costness, and difficulties to implement micro‐nano processing equipment have been effectively solved, achieving rapid closed‐loop verification from concept to physical object. The effectiveness of this framework has been verified through multi‐dimensional student feedback. The framework not only cultivates students' interdisciplinary integration abilities in the fields of digital manufacturing and industrial IoT, but also provides an extensible teaching practice path for engineering education to adapt to technological development.

Computer Applications in Engineering EducationVol. 34(3)
East China University of Science and Technology (CN), Shanghai University of Medicine and Health Sciences (CN), Shanghai Huayi Group (China) (CN)
National Natural Science Foundation of China
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Nanotechnology research and applications
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