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Tracking Soccer Game Play with Big Data Streaming, Internet of Things, and Complex Event Processing

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Tracking Soccer Game Play with Big Data Streaming, Internet of Things, and Complex Event Processing

· IoT Zone
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soccer field

Teams gain a competitive edge by analyzing Big Data streams. By using complex event processing and MapReduce based technologies, teams can improve performance. By establishing a feedback loop, your team can visualize business activity, understand impact, and take positive actions.

Big data Life Cycle

One powerful Big Data streaming example, soccer match activity data captured by embedded sensors were streamed and analyzed to understand how player actions impact soccer play.

Soccer players, race car drivers, energy buyers, stock traders, and digital marketers gain a competitive edge by acting on strategic and tactical intelligence recommendations.  By connecting intelligent controllers to a multitude of Internet of Things (IoT) devices (i.e. soccer balls, shoes, cellphones, and turbines) and connected business information feeds (i.e. clearing houses, weather services, and ad networks), teams can aggregate Big Data, create Big Data streams, and trigger events that influence workflow and enhance performance.

In the DEBS challenge, teams bridged soccer game play to Internet of Things and analytics.  Sensors placed in shoes, goal mitts, and soccer balls streamed spatial, vector, and temporal information toward Big Data stream receivers.  The solution processed data stream events in real time to understand play actions and visual game play (through heat maps).  Teams can use the analytic visualization to recommend performance improvements.


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Published at DZone with permission of Chris Haddad, DZone MVB. See the original article here.

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