IoT Platform for Sports Analytics

Author:

Gowda Mahanth1,Dhekne Ashutosh2,Shen Sheng2,Choudhury Romit Roy2,Yang Sharon Xue3,Yang Lei3,Golwalkar Suresh3,Essanian Alexander3

Affiliation:

1. Pennsylvania State University

2. University of Illinois at Urbana-Champaign

3. Intel

Abstract

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.

Publisher

Association for Computing Machinery (ACM)

Reference11 articles.

1. D2m. http://d2m-inc.com/. D2m. http://d2m-inc.com/.

2. Ellipsoid or sphere fitting for sensor calibration. www.st.com/resource/en/design_tip/dm00286302.pdf Ellipsoid or sphere fitting for sensor calibration. www.st.com/resource/en/design_tip/dm00286302.pdf

3. Hawk-eye. https://en.wikipedia.org/wiki/Hawk-Eye/. Hawk-eye. https://en.wikipedia.org/wiki/Hawk-Eye/.

4. Inertial measurement unit. https://stanford.edu/class/ee267/lectures/lecture9.pdf Inertial measurement unit. https://stanford.edu/class/ee267/lectures/lecture9.pdf

5. Motioncapturesystems-vicon. https://www.vicon.com/. Motioncapturesystems-vicon. https://www.vicon.com/.

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