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Physical Education Teaching Strategy under Internet of Things Data Computing Intelligence Analysis.

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This study introduces an Internet of Things (IoT) based video and image recognition system to enhance tennis coaching. The system significantly improved students' serving abilities compared to traditional methods.

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Area of Science:

  • Sports Science
  • Educational Technology

Background:

  • Tennis is a popular sport, but traditional teaching methods have limitations.
  • Optimizing tennis instruction is crucial for improving player performance and teaching quality.

Purpose of the Study:

  • To develop and validate an Internet of Things (IoT) video and image recognition system for tennis instruction.
  • To compare the effectiveness of the new system against traditional teaching methods.

Main Methods:

  • Developed a tennis teaching system utilizing image processing and IoT for action recognition.
  • Divided students into an experimental group (using the IoT system) and a control group (traditional methods).
  • Measured and compared key biomechanical factors (service throwing height, elbow angle, knee bending) against elite players.

Main Results:

  • The experimental group using the IoT system showed significant improvements in serving ability.
  • Students trained with the IoT system outperformed those in the control group.
  • The system provided a basis for analyzing and improving tennis techniques.

Conclusions:

  • The IoT video and image recognition system effectively enhances tennis teaching quality.
  • This technology offers a novel approach for physical education and innovative tennis coaching strategies.