A novel IoT-based health and tactical analysis model with fog computing

Area of Science:

• Sports Science
• Computer Science
• Network Engineering

Background:

• Sports competitions pose risks like player injury and health emergencies.
• Real-time strategic analysis is crucial for team performance.
• Existing systems lack integrated health monitoring and advanced analytics.

Purpose of the Study:

• To propose a novel fog computing and Internet of Things (IoT) based architecture.
• To enhance player and spectator safety through continuous health monitoring.
• To enable advanced strategic analysis for improved team performance.

Main Methods:

• Utilized sensors (blood pressure, temperature, heart rate, location) for player and spectator monitoring.
• Implemented a fog computing layer for low-latency data processing and analysis.
• Employed a modified priority queue algorithm for efficient task management in the fog layer.
• Integrated Federated Lightweight Authentication of Things (FLAT) for data security and privacy.
• Leveraged a Software Defined Network (SDN) controller with blockchain for data integrity.

Main Results:

• The proposed architecture enables real-time health monitoring and strategic insights.
• Low-latency processing ensures timely information delivery to technical staff and doctors.
• Enhanced data security, confidentiality, and integrity are achieved through FLAT and blockchain.
• The system effectively supports the development of new technical strategies.

Conclusions:

• The fog computing and IoT architecture offers a robust solution for sports event safety and performance optimization.
• Real-time data analytics and secure data management are vital for modern sports.
• This integrated approach can significantly reduce risks and improve decision-making in sports competitions.