BBAuthors: Zhang, H.; Advisor: -; Participants: Fu, Z.; Shu, K. (2019)
With the development of Internet of Things (IoT) technology and various sensing technologies, some newer ways of perceiving people and the environment have emerged. Commercial wearable sensing devices integrate a variety of sensors that can play a signi cant role in motion capture and behavioral analysis. This paper proposes a solution for recognizing human motion in ping-pong using a commercial smart watch. We developed a data acquisition system based on the IoT architecture to obtain data relating to areas such as acceleration, angular velocity, and magnetic induction of the watch. Based on the features of the extracted data, experiments were performed using major machine learning classi cation algorithms including k-nearest neighbor, support vector machine, Naive Bayes, logistic ... 
