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Data Collection and Analysis of Track and Field Athletes' Behavior Based on Edge Computing and Reinforcement Learning
2021
Mobile Information Systems
With the development of multimedia technology, the computer auxiliary system has become an effective means of daily training in track and field. This paper designs a data acquisition and analysis system for track and field athletes. The system uses sensor modules attached to the athlete's body to collect movement data for analysis. The whole system is implemented by edge computing architecture. In order to reduce average response time, the DDPG algorithm is used to optimize the resource
doi:10.1155/2021/9981767
doaj:45c347bc68ce4ad08dbf8cbb168e28a3
fatcat:nnjh54mv7zdklo335zdpsd2c44