Bringing IoT to sports analytics

Mahanth Gowda, Ashutosh Dhekne, Sheng Shen, Romit Roy Choudhury, Xue Yang, Lei Yang, Suresh Golwalkar, Alexander Essanian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

This paper explores the possibility of bringing IoT to sports analytics, particularly to the game of Cricket. We develop solutions to track a ball’s 3D trajectory and spin with inexpensive sensors and radios embedded in the ball. Unique challenges arise rendering existing localization and motion tracking solutions inadequate. Our system, iBall, mitigates these problems by fusing disparate sources of partial information – wireless, inertial sensing, and motion models – into a non-linear error minimization framework. Measured against a mm-level ground truth, 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 any calibration or training, hence we expect the core techniques to extend to other sports like baseball, with some domain-specific modifications.

Original languageEnglish (US)
Title of host publicationProceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017
PublisherUSENIX Association
Pages499-513
Number of pages15
ISBN (Electronic)9781931971379
StatePublished - Jan 1 2017
Event14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017 - Boston, United States
Duration: Mar 27 2017Mar 29 2017

Publication series

NameProceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017

Conference

Conference14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017
CountryUnited States
CityBoston
Period3/27/173/29/17

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'Bringing IoT to sports analytics'. Together they form a unique fingerprint.

Cite this