{"title":"实时足球分析与StreamTeam:演示","authors":"L. Probst, Frederik Brix, H. Schuldt, M. Rumo","doi":"10.1145/3093742.3095089","DOIUrl":null,"url":null,"abstract":"In the last years, the analysis of data in sports has received considerable attention, especially due to the wide availability of unobtrusive wearable sensors. While most approaches focus on the (post-hoc) monitoring of individuals, a big and still largely unsolved challenge is the monitoring of the tactical behavior and tactical compliance of entire teams in real-time. In this paper, we introduce STREAMTEAM, a novel and extensible workflow-based approach to analyze data streams and to detect complex team events in real-time. We show the application of STREAMTEAM to data sets coming from sensors attached to players of football teams.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Real-Time Football Analysis with StreamTeam: Demo\",\"authors\":\"L. Probst, Frederik Brix, H. Schuldt, M. Rumo\",\"doi\":\"10.1145/3093742.3095089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the last years, the analysis of data in sports has received considerable attention, especially due to the wide availability of unobtrusive wearable sensors. While most approaches focus on the (post-hoc) monitoring of individuals, a big and still largely unsolved challenge is the monitoring of the tactical behavior and tactical compliance of entire teams in real-time. In this paper, we introduce STREAMTEAM, a novel and extensible workflow-based approach to analyze data streams and to detect complex team events in real-time. We show the application of STREAMTEAM to data sets coming from sensors attached to players of football teams.\",\"PeriodicalId\":325666,\"journal\":{\"name\":\"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3093742.3095089\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3093742.3095089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In the last years, the analysis of data in sports has received considerable attention, especially due to the wide availability of unobtrusive wearable sensors. While most approaches focus on the (post-hoc) monitoring of individuals, a big and still largely unsolved challenge is the monitoring of the tactical behavior and tactical compliance of entire teams in real-time. In this paper, we introduce STREAMTEAM, a novel and extensible workflow-based approach to analyze data streams and to detect complex team events in real-time. We show the application of STREAMTEAM to data sets coming from sensors attached to players of football teams.