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Intelligent System of Game-Theory-Based Decision Making in Smart Sports Industry
ACM Transactions on Intelligent Systems and Technology ( IF 5 ) Pub Date : 2021-04-21 , DOI: 10.1145/3447986
Munish Bhatia 1
Affiliation  

Internet of Things (IoT) technology backed by Artificial Intelligence (AI) techniques has been increasingly utilized for the realization of the Industry 4.0 vision. Conspicuously, this work provides a novel notion of the smart sports industry for provisioning efficient services in the sports arena. Specifically, an IoT-inspired framework has been proposed for real-time analysis of athlete performance. IoT data is utilized to quantify athlete performance in the terms of probability parameters of Probabilistic Measure of Performance (PMP) and Level of Performance Measure (LoPM). Moreover, a two-player game-theory-based mathematical framework has been presented for efficient decision modeling by the monitoring officials. The presented model is validated experimentally by deployment in District Sports Academy (DSA) for 60 days over four players. Based on the comparative analysis with state-of-the-art decision-modeling approaches, the proposed model acquired enhanced performance values in terms of Temporal Delay, Classification Efficiency, Statistical Efficacy, Correlation Analysis, and Reliability.

中文翻译:

基于博弈论的智能体育产业智能决策系统

以人工智能 (AI) 技术为后盾的物联网 (IoT) 技术已越来越多地用于实现工业 4.0 愿景。值得注意的是,这项工作为在体育领域提供高效服务提供了智能体育产业的新概念。具体来说,已经提出了一个受物联网启发的框架,用于实时分析运动员的表现。物联网数据用于根据表现概率测量 (PMP) 和表现测量水平 (LoPM) 的概率参数来量化运动员的表现。此外,还提出了一个基于两人博弈论的数学框架,用于监测官员的有效决策建模。所提出的模型通过在地区体育学院 (DSA) 部署 60 天的四名球员进行了实验验证。
更新日期:2021-04-21
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