Mahanth K. Gowda, Ashutosh Dhekne, Sheng Shen, Romit Roy Choudhury, Sharon Xue Yang, Lei Yang, S. Golwalkar, Alexander Essanian
{"title":"物联网体育分析平台","authors":"Mahanth K. Gowda, Ashutosh Dhekne, Sheng Shen, Romit Roy Choudhury, Sharon Xue Yang, Lei Yang, S. Golwalkar, Alexander Essanian","doi":"10.1145/3191789.3191793","DOIUrl":null,"url":null,"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.","PeriodicalId":213775,"journal":{"name":"GetMobile Mob. Comput. Commun.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"IoT Platform for Sports Analytics\",\"authors\":\"Mahanth K. Gowda, Ashutosh Dhekne, Sheng Shen, Romit Roy Choudhury, Sharon Xue Yang, Lei Yang, S. Golwalkar, Alexander Essanian\",\"doi\":\"10.1145/3191789.3191793\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":213775,\"journal\":{\"name\":\"GetMobile Mob. Comput. Commun.\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GetMobile Mob. Comput. Commun.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3191789.3191793\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GetMobile Mob. Comput. Commun.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3191789.3191793","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.