A Distributed Data Integration Fault Tolerant Platform for Performance Optimization in Shooting Sports

In today’ s fast-paced and highly competitive landscape, there is an ever-growing need to enhance the precision, agility, and overall performance of athletes, especially in sports that demand high levels of accuracy and coordination, such as shooting. With the rapid advancement of technology, the role of data analytics in athletic training has gained substantial attention, serving as a powerful tool to elevate athlete performance. This study aims to develop an integrated data platform to support a more precise and holistic approach to training for shooting athletes. By seamlessly combining various types of response and performance data - such as manual reaction times, shooting response times, eye-tracking data, video analyses, and biomechanical data-with a distributed Elasticsearch (ES) data synchronization system, the platform enables comprehensive data collection and analysis. This integration provides invaluable insights into the training status and individual differences of athletes, offering scientific, data-driven guidance for coaches. Furthermore, a robust distributed disaster recovery system is implemented by synchronizing two Elasticsearch clusters with a MySQL database. Although the primary and backup switch mechanisms are still under development, an automated script continuously monitors system health, allowing for rapid failover to backup clusters when necessary. This research opens new avenues in the application of data-driven platforms for athletic performance enhancement, providing a resilient infrastructure for continuous, uninterrupted data analytics, and setting a foundation for future enhancements in sports training methodologies.