Modern Advances in Artificial Intelligence Across the Athletic Domain

IF 1.5 4区计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Concurrency and Computation-Practice & Experience Pub Date : 2025-04-12 DOI:10.1002/cpe.70068

Xin Zhao, Haotian Zheng, Qiyun Zhang

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引用次数: 0

Abstract

Artificial intelligence (AI) is a branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence, such as learning, reasoning, and understanding natural language. The integration of AI into the athletic domain has revolutionized various aspects, from performance analysis to fan engagement and operational efficiency. Recent advancements have showcased the potential of AI technologies, including machine learning, computer vision, and data analytics, to enhance athletic performance, optimize training regimens, and provide personalized experiences for fans. This review examines the current landscape of AI applications in athletics, highlighting innovative use cases such as player performance monitoring, injury prevention, game strategy optimization, and audience engagement. It underscores the transformative impact of AI on traditional athletic practices while also addressing the challenges and ethical concerns associated with its growing adoption. Future directions for research and development in this field are also discussed, emphasizing the need for ongoing collaboration between technologists and athletic professionals.

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体育领域人工智能的现代进展

人工智能（AI）是计算机科学的一个分支，专注于创建能够执行通常需要人类智能的任务的系统，例如学习、推理和理解自然语言。将人工智能整合到体育领域已经彻底改变了各个方面，从表现分析到球迷参与和运营效率。最近的进展展示了人工智能技术的潜力，包括机器学习、计算机视觉和数据分析，可以提高运动员的表现，优化训练方案，并为球迷提供个性化的体验。本文回顾了人工智能在田径运动中的应用现状，重点介绍了一些创新用例，如运动员表现监控、伤病预防、游戏策略优化和观众参与。它强调了人工智能对传统体育实践的变革性影响，同时也解决了人工智能日益普及所带来的挑战和伦理问题。本文还讨论了该领域未来的研究和发展方向，强调了技术专家和运动专业人员之间持续合作的必要性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Concurrency and Computation-Practice & Experience 工程技术-计算机：理论方法

CiteScore

5.00

自引率

10.00%

发文量

664

审稿时长

9.6 months

期刊介绍： Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.