AI-driven communication networks for real-time sports analytics and fan engagement in edge-IoT environments

Puntos clave

• The research aims to explore the implementation of AI-driven communication networks to enhance real-time sports analytics and fan engagement.
• Developed AI-based communication frameworks for real-time data processing in sports environments.
• Evaluated the impact of these networks on fan engagement metrics and analytical accuracy.
• Utilized edge-IoT infrastructure to optimize data transmission and processing.
• AI-driven networks improved real-time analytics by 30%, enhancing decision-making speed (p<0.01).
• Fan engagement metrics increased by 40% post-implementation, indicating higher interaction rates (p<0.05).
• The edge-IoT approach reduced latency by 50%, making instant updates possible.