Evaluation of Tennis Teaching Effect Using Optimized DL Model with Cloud Computing System

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Author(s)

Sai Srinivas Vellela 1 M Venkateswara Rao 2 Srihari Varma Mantena 3 M V Jagannatha Reddy 4 Ramesh Vatambeti 5,* Syed Ziaur Rahman 6

1. Department of CSE-Data Science, Chalapathi Institute of Technology, Guntur 522016, India

2. Department of CSE, NRI Institute of Technology, Vijayawada 521212, India

3. Department of Computer Science and Engineering, Sagi Rama Krishnam Raju Engineering College, Bhimavaram 534204, India

4. Department of CSE, GITAM University, Bengaluru Campus, Bengaluru 561203, India

5. School of Computer Science and Engineering, VIT-AP University, Vijayawada-522237, India

6. Faculty of Information Technology, Majan University College (Affiliated to University of Bedfordshire, United Kingdom), Muscat- 710, Oman

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2024.02.02

Received: 18 Jul. 2023 / Revised: 19 Aug. 2023 / Accepted: 13 Sep. 2023 / Published: 8 Apr. 2024

Index Terms

Bidirectional Long Short-Term Memory, Table Tennis shadow-play, Improved dragonfly algorithm, Forehand stroke, Home sports activity

Abstract

Evidence from psychology and behaviour therapy shows that engaging in sports activities at home might help alleviate stress and depression during COVID-19 lockdown periods. A clever virtual coach that provides table tennis instruction at a low cost without invading privacy might be a great way to maintain a healthy lifestyle without leaving the house. In this article, we look at creating the second main constituent of the virtual-coach table tennis shadow-play training scheme: an evaluation system for the effectiveness of the forehand stroke. This research was carried out to demonstrate the efficacy of the suggested bidirectional long-short-term memory (BLSTM) model in assessing the table tennis forehand shadow-play sensory data supplied by the authors in comparison with LSTM time-series investigation approaches. Information was collected by tracking the rackets of 16 players as they performed forehand strokes and assigning assessment ratings to each stroke based on the input of three instructors. The scientists looked at how the hyperparameter values, which are chosen via an optimisation approach, affected the behaviour of DL models. The adaptive learning differential approach has been introduced to enhance the functionality of the standard dragonfly algorithm. Optimal BLSTM settings are selected with the help of the enhanced dragonfly algorithm (IDFOA).  
The experimental findings of this study indicate that the BLSTM-IDFOA is the most effective regression approach currently available.

Cite This Paper

Sai Srinivas Vellela, M Venkateswara Rao, Srihari Varma Mantena, M V Jagannatha Reddy, Ramesh Vatambeti, Syed Ziaur Rahman, "Evaluation of Tennis Teaching Effect Using Optimized DL Model with Cloud Computing System", International Journal of Modern Education and Computer Science(IJMECS), Vol.16, No.2, pp. 16-28, 2024. DOI:10.5815/ijmecs.2024.02.02

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