The Application of Artificial Intelligence Technology in Physical Education

Wen, Bo

doi:10.1007/978-981-15-5959-4_98

Cited by 5 publications

(6 citation statements)

References 6 publications

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“…Figure 7 shows the comparison of student satisfaction of the proposed method and the traditional approaches. With the proposed physical education system, the student showed the highest satisfaction of 97% as compared to the satisfaction levels of models developed by Casey et al [8], Kang et al [18], Wang et al [3], and Wen [20], respectively.…”

Section: Mobile Information Systemsmentioning

confidence: 78%

“…Figure 2 shows the comparative analysis of the accuracy of the existing and the proposed methods. We compared the proposed physical education system with that of Casey et al [8], Kang et al [18], Wang et al 4 Mobile Information Systems [3], and Wen [20], respectively. The proposed system obtained the highest accuracy of 98% as compared to other models.…”

Section: Performance Analysismentioning

confidence: 99%

“…Figure 3 shows the comparative analysis of energy efficiency for the existing and the proposed methods. The proposed physical education was compared with that of Casey et al [8], Kang et al [18], Wang et al [3], and Wen [20], respectively. The highest energy efficiency of 93% was shown by the proposed system.…”

Section: Energy Efficiencymentioning

confidence: 99%

“…Figure 4 shows the comparative analysis of the security level of the proposed system and the conventional approaches. We compared the security level of the proposed system with the security of the systems developed by Casey et al [8], Kang et al [18], Wang et al [3], and Wen [20], respectively. The proposed system showed the highest security level of 86% as compared to the security levels of the system proposed by Casey et al [8], Kang et al [18], Wang et al [3], and Wen [20] which are 88%, 89%, 91%, and 92%, respectively.…”

Section: Mobile Information Systemsmentioning

confidence: 99%

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The Application of 5G Network Technology in the Innovative Development of Physical Education

Wang

2022

Mobile Information Systems

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The rapid development of information technology is changing people’s work, learning, and lifestyle and bringing new development space to education. Physical education is an important component of the university education system. The goal of physical education is to increase the physical fitness of the students and promote their advancement. In the context of the recent evolution of the social economy, the fifth-generation (5G) network technology is increasingly being deployed in many fields which may assist students to actively partake in physical education and promote successful physical education development. This study proposes an innovative framework based on 5G network technology for the development of physical education. The Internet of Things (IoT) technology is used to achieve long-term data collecting and real-time data monitoring, and a unique cuckoo search firefly optimization algorithm (CSFOA) is presented to improve data transmission efficiency. The performance of the system is assessed in terms of accuracy, energy efficiency, security level, error rate, and student satisfaction, respectively. Results confirm that the proposed system has certain practical effects and has the potential to optimize the process of physical education development.

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Section: Mobile Information Systemsmentioning

confidence: 78%

Section: Performance Analysismentioning

confidence: 99%

Section: Energy Efficiencymentioning

confidence: 99%

Section: Mobile Information Systemsmentioning

confidence: 99%

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The Application of 5G Network Technology in the Innovative Development of Physical Education

Wang

2022

Mobile Information Systems

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“…Artificial intelligence (AI) began to have a profound impact on human existence as science and technology advanced. There has also been a steady increase in the use of AI for sports education [ 38 ]. This is a byproduct and an unavoidable outcome of the new exploration mode of PE instruction, as traditional education has no place in the current time.…”

Section: Methodsmentioning

confidence: 99%

Analysis on the Reform and Development of Physical Education Services in the Context of 5G Connected Communication

Wang

Yan

Zhang

et al. 2022

Computational Intelligence and Neuroscience

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With the continuous growth of science and technology, mankind has entered the fifth-generation (5G) era. In this background, the development of many fields will face great opportunities and challenges, including the field of physical education (PE). The traditional teaching mode, method, and contents of PE are difficult to adapt to the development needs of the 5G era. Therefore, it is of great significance to study the PE teaching reform in the era of “5G education.” Moreover, integrating 5G technology and PE may benefit students, educators, and the entire PE system. This study offers an in-depth investigation of the reforms and development of PE services under the background 5G interconnected communications. The reforms of PE and services are examined using the most up-to-date 5G technologies. Four 5G methodologies which include model-based practice (MBP), virtual reality (VR), the Internet of Things (IoT), and artificial intelligence (AI) are analyzed, and for the comparative study, performance indicators such as cost reduction, energy efficiency, and security level are measured. When compared to other strategies, IoT-based physical education is found to be more efficient in terms of these parameters. The 5G-driven PE will provide students with objective, fair, and diversified education, and adaptive learning services to promote the overall development of students.

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RETRACTED: Recognition of students’ behavior states in classroom based on improved MobileNetV2 algorithm

Cao

Liu

Hao

et al. 2021

International Journal of Electrical Engineering & Education

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Analyzing and learning students' behavior states in classroom plays a positive role in understanding and improving the teaching effectiveness. Meanwhile, the application of lightweight network to pattern recognition has become a trend with the development of mobile networks. In order to improve the recognition accuracy of the lightweight network model MobileNetV2 and reduce the computational cost and delay caused by extracting rich features, an improved lightweight network model based on MobileNetV2 is proposed, in which an improved reverse residual module (C-Inverted residual block) is applied to replace the traditional module. In the improved reverse residual module, channel split operation is added to reduce MAC, and channel shuffle operations are used to promote information exchange and channel fusion. Experiments were carried out on Pascal VOC 2007 detection data set to test the general performance of the proposed improved model. Under the operation limits of 140 MFLOPS, 40 MFLOPS and 20 MFLOPS, mean average precision (mAP) of the improved MobileNetV2 algorithm increased by 1.2%, 2.2% and 4.3% compared with MobileNetV2. While the recognition accuracy of the proposed network model on self-made dataset of student classroom behavior states is 4.6% and 3.7% higher than that of MobileNetV1 and MobileNetV2 respectively, and the average recognition rate of students' classroom behavior states can be up to 92.7%. The results of this research combined with mobile networks would be expected to be used to evaluate teaching and learning effects and promote teaching quality improvement.

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The Application of Artificial Intelligence Technology in Physical Education

Cited by 5 publications

References 6 publications

The Application of 5G Network Technology in the Innovative Development of Physical Education

The Application of 5G Network Technology in the Innovative Development of Physical Education

Analysis on the Reform and Development of Physical Education Services in the Context of 5G Connected Communication

RETRACTED: Recognition of students’ behavior states in classroom based on improved MobileNetV2 algorithm

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