short-paper

Herakles: real-time sport analysis using a distributed data stream management system

Authors:

Timo Michelsen,

Michael Brand,

Carsten Cordes,

H.-Jürgen AppelrathAuthors Info & Claims

DEBS '15: Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems

Pages 356 - 359

https://doi.org/10.1145/2675743.2776775

Published: 24 June 2015 Publication History

Get Access

Abstract

Tactical decisions profoundly characterize team sports like soccer or basketball. Analyses of matches and training sessions (e.g., mileage or pass completion rate of a player) become more and more important for those tactical decisions. Most of the analyses are video-based, resulting in high operating expenses. Additionally, a highly specialized system with a huge amount of system resources like processors and memory is needed. Typically, analysts present the results of the video data analysis in time-outs (e.g., in the half-time break of a soccer match). However, coaches often desire to view statistics in real-time during the match.

In this paper, we demonstrate Herakles, a system for live sport analysis using streaming sensor data and a Peer-to-Peer network of conventional and low-cost private machines. Since sensor data is typically of high volume and velocity, Herakles uses OdysseusP2P, a distributed data stream management system, for processing these streams in real-time. Since the results of the data stream processing are intended for coaches, the front-end of Herakles is an application for mobile devices like smartphones or tablets. With Herakles, a coach is able to view individual sport statistics during the game at the sideline to make immediate tactical decisions.

References

[1]

Debs 2013. http://www.orgs.ttu.edu/debs2013 (visited: 04/30/15).

Google Scholar

[2]

Improving performance with smarter soccer analytics using sap hana. http://hana.sap.com/customers/customer-stories/tsg1899hoffenheim.html (visited: 29/04/15).

Google Scholar

[3]

Keymotion automated sports production. http://www.keemotion.com/ (visited: 04/29/15).

Google Scholar

[4]

Synergy sports technology -- homepage. http://corp.synergysportstech.com/ (visited: 04/29/15).

Google Scholar

[5]

H.-J. Appelrath, D. Geesen, M. Grawunder, T. Michelsen, and D. Nicklas. Odysseus: a highly customizable framework for creating efficient event stream management systems. DEBS '12, pages 367--368. ACM, 2012.

Digital Library

Google Scholar

[6]

C. Baum. Sports analysis and testing system, 2000. US Patent 6,042,492.

Google Scholar

[7]

M. Brand, T. Brandt, C. Cordes, M. Wilken, and T. Michelsen. Herakles: A system for sensor-based live sport analysis using private peer-to-peer networks. 2015.

Google Scholar

[8]

M. Leo, N. Mosca, P. Spagnolo, P. L. Mazzeo, T. D'Orazio, and A. Distante. Real-time multiview analysis of soccer matches for understanding interactions between ball and players. In Proceedings of the 2008 international conference on Content-based image and video retrieval, pages 525--534. ACM, 2008.

Digital Library

Google Scholar

[9]

T. Michelsen. Data stream processing in dynamic and decentralized peer-to-peer networks. In Proceedings of the 2014 SIGMOD PhD symposium. ACM, 2014.

Digital Library

Google Scholar

[10]

C. Mutschler, H. Ziekow, and Z. Jerzak. The debs 2013 grand challenge. In Proceedings of the 7th ACM International Conference on Distributed Event-based Systems, DEBS '13, pages 289--294, New York, NY, USA, 2013. ACM.

Digital Library

Google Scholar

[11]

A. F. Smeaton, D. Diamond, P. Kelly, K. Moran, K.-T. Lau, D. Morris, N. Moyna, N. E. O'Connor, and K. Zhang. Aggregating multiple body sensors for analysis in sports. 2008.

Google Scholar

[12]

T. von der Grün, N. Franke, D. Wolf, N. Witt, and A. Eidloth. A real-time tracking system for football match and training analysis. In Microelectronic Systems, pages 199--212. Springer, 2011.

Crossref

Google Scholar

Cited By

View all

Akinci Y(2023)Examining the Differences Between Playoff Teams and Non-Playoff Teams in Men’s Euroleague; Play-Type Statistics PerspectiveSage Open10.1177/2158244023122015513:4Online publication date: 22-Dec-2023
https://doi.org/10.1177/21582440231220155
Rana MMittal V(2021)Wearable Sensors for Real-Time Kinematics Analysis in Sports: A ReviewIEEE Sensors Journal10.1109/JSEN.2020.301901621:2(1187-1207)Online publication date: 15-Jan-2021
https://doi.org/10.1109/JSEN.2020.3019016
Probst LSchuldt HSeidenschwarz PRumo M(2020)StreamTeam-Football: Analyzing Football Matches in Real-Time on the Basis of Position Streams2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9377914(637-644)Online publication date: 10-Dec-2020
https://doi.org/10.1109/BigData50022.2020.9377914
Show More Cited By

Index Terms

Herakles: real-time sport analysis using a distributed data stream management system
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Graphical user interfaces
2. Information systems

Recommendations

BMQ-Processor: A High-Performance Border-Crossing Event Detection Framework for Large-Scale Monitoring Applications

In this paper, we present BMQ-Processor, a high-performance Border-Crossing Event (BCE) detection framework for large-scale monitoring applications. We first characterize a new query semantics, namely, Border Monitoring Query (BMQ), which is useful for ...
Generic windowing support for extensible stream processing systems

Stream processing applications process high volume, continuous feeds from live data sources, employ data-in-motion analytics to analyze these feeds, and produce near real-time insights with low latency. One of the fundamental characteristics of such ...
Spatio-Temporal Analysis of Team Sports

Team-based invasion sports such as football, basketball, and hockey are similar in the sense that the players are able to move freely around the playing area and that player and team performance cannot be fully analysed without considering the movements ...

Comments

Information & Contributors

Information

Published In

DEBS '15: Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems

June 2015

385 pages

ISBN:9781450332866

DOI:10.1145/2675743

General Chairs:
Frank Eliassen
University of Oslo, Norway
,
Roman Vitenberg
University of Oslo, Norway

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 June 2015

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Short-paper

Conference

DEBS '15

Sponsor:

DEBS '15: The 9th ACM International Conference on Distributed Event-Based Systems

June 29 - July 3, 2015

Oslo, Norway

Upcoming Conference

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
246
Total Downloads

Downloads (Last 12 months)19
Downloads (Last 6 weeks)3

Reflects downloads up to 03 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Akinci Y(2023)Examining the Differences Between Playoff Teams and Non-Playoff Teams in Men’s Euroleague; Play-Type Statistics PerspectiveSage Open10.1177/2158244023122015513:4Online publication date: 22-Dec-2023
https://doi.org/10.1177/21582440231220155
Rana MMittal V(2021)Wearable Sensors for Real-Time Kinematics Analysis in Sports: A ReviewIEEE Sensors Journal10.1109/JSEN.2020.301901621:2(1187-1207)Online publication date: 15-Jan-2021
https://doi.org/10.1109/JSEN.2020.3019016
Probst LSchuldt HSeidenschwarz PRumo M(2020)StreamTeam-Football: Analyzing Football Matches in Real-Time on the Basis of Position Streams2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9377914(637-644)Online publication date: 10-Dec-2020
https://doi.org/10.1109/BigData50022.2020.9377914
Probst LRauschenbach FSchuldt HSeidenschwarz PRumo M(2018)Integrated Real-Time Data Stream Analysis and Sketch-Based Video Retrieval in Team Sports2018 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2018.8622592(548-555)Online publication date: Dec-2018
https://doi.org/10.1109/BigData.2018.8622592
Probst LBrix FSchuldt HRumo M(2017)Real-Time Football Analysis with StreamTeamProceedings of the 11th ACM International Conference on Distributed and Event-based Systems10.1145/3093742.3095089(319-322)Online publication date: 8-Jun-2017
https://dl.acm.org/doi/10.1145/3093742.3095089
Reno VMosca NNitti MGuaragnella CD'Orazio TStella E(2016)Real-time tracking of a tennis ball by combining 3D data and domain knowledge2016 1st International Conference on Technology and Innovation in Sports, Health and Wellbeing (TISHW)10.1109/TISHW.2016.7847774(1-7)Online publication date: Dec-2016
https://doi.org/10.1109/TISHW.2016.7847774
Surm HRussmeier NGrawunder MNicklas DZielinski O(2016)Experiences with Sensor-Based Research for Critical, Socio-technical Systems2016 17th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM.2016.41(214-219)Online publication date: Jun-2016
https://doi.org/10.1109/MDM.2016.41

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

BMQ-Processor: A High-Performance Border-Crossing Event Detection Framework for Large-Scale Monitoring Applications

Generic windowing support for extensible stream processing systems

Spatio-Temporal Analysis of Team Sports

Comments

Information

Published In

Sponsors

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Conference

Upcoming Conference

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations