DESIGN AND DEVELOPMENT OF AI CLOUD-BASED VIDEO RECORDING SYSTEM FOR ATHLETE MOVEMENTS

Abstract

This paper presents the design and development of an AI cloud-based video recording system for athlete move- ment analysis. The proposed system utilizes the Wemos D1 Mini microcontroller as the core hardware platform and a GoPro cam- era for high-quality video capture. By leveraging the capabilities of these components, the system enables real-time video re- cording of athlete movements, facilitating detailed performance analysis and feedback. Furthermore, the system seamlessly inte- grates with Amazon Web Services (AWS) IoT Core, enabling efficient data transmission and storage in the cloud. Through re- search and development, both the hardware and software components of the system were designed and implemented, ensuring robust performance and scalability. Experiments demonstrate the efficacy of the proposed solution in capturing high-fidelity video footage of athlete movements and securely transmitting it to the cloud for further analysis. This research lays the foundation for advanced athlete monitoring systems, offering valuable insights for coaches, trainers, and sports scientists to enhance training regimens and optimize performance.