Key points are not available for this paper at this time.
This paper is an experience report on IoT platforms for sports analytics. In our prior work 11, we proposed iBall, a system that explores the possibility of bringing IoT to sports analytics, particularly to the game of Cricket. iBall develops solutions to track a ball's 3D trajectory and spin with inexpensive sensors and radios embedded in the ball. Towards this end, iBall performs fusion of wireless and inertial sensory data and integrates them into physics-based motion models of a ball in flight. The median ball location error is at 8cm while rotational error remains below 12° even at the end of the flight. The results do not rely on training, hence we expect the core techniques to extend to other sports like baseball, with some domain-specific modifications.
Gowda et al. (2018) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: