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Research Article | Open Access

Modern technology, artificial intelligence, machine learning and internet of things based revolution in sports by employing graph theory matrix approach

Lingtao Wen1Zebo Qiao2Jun Mo1( )
Guangzhou Huashang College, Guangzhou 511300, Guangdong, China
Guangdong University of Finance & Economics, Guangzhou 510320, Guangdong, China
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Abstract

The sports industry is gaining popularity with time and all the countries are investing a lot of money for fame and entertainment around the world. To ensure the high quality of sports, modern techniques such as machine learning (ML), artificial intelligence (AI) and the Internet of Things (IoT) are playing a very optimistic role. Various IoT-grounded smart sensors are implemented with integration in AI and ML for the safety and high performance of the players. Based on the numerous applications of modern technologies, it is very convenient to capture different body movements of the players and avoid any severe injuries and long-term health issues. AI and IoT-driven smart devices are revolutionizing the analysis of athletes' training and performance, offering precise insights for their improvement. This article delved into the remarkable strides made in scientific sports, highlighting how computer-based elements are reshaping the sports landscape for athletes and spectators alike. These innovations enable real-time health monitoring, prevent accidents, capture diverse postures and analyze sporting outcomes. By extensively reviewing existing literature, key features have been identified and prioritized. Using the graph theory matrix approach (GTMA), this piece compared and ranks available alternatives based on these selected features. Moreover, the parameter matrix and normalized matrix were reported in tabulated form and the ranks for ten paradigms are illustrated graphically for better visualization.

CLC number: Researcharticle

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AIMS Mathematics
Pages 1211-1226

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Cite this article:
Wen L, Qiao Z, Mo J. Modern technology, artificial intelligence, machine learning and internet of things based revolution in sports by employing graph theory matrix approach. AIMS Mathematics, 2024, 9(1): 1211-1226. https://doi.org/10.3934/math.2024060

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Received: 16 October 2023
Revised: 21 November 2023
Accepted: 24 November 2023
Published: 15 January 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)