AL ML

Our customer here comes from a techno sports background. They provide services to various sports agencies and have entered the consumer market offering different products for the segment.

Sports Tech, AI & ML, Mobile App Development.
AI-driven game analysis, real-time streaming, AR-based player tracking

Project Details

The client was seeking an application for iOS and Android platforms that would allow users to follow a game in real-time as well as participate in bets, and provide real-time game analysis to the players. Horizontal scalability of the application was further desired.

AI Ml Case Study

Problem

  • The client wanted to develop an app for both Android and iOS platforms. This app would enable users to view the game’s updates in real-time and allow them to participate in bets as well.
  • The requirement was to live stream the game and allow the user to view the game in real-time. 
  • The client was also facing a challenge in terms of video streaming, streaming support was required even in case of a throttling network.
  • The app was required to cater to the needs of players as well. The client wanted the app to provide real-time analysis to the player as well as give them information about how the shot got played, factoring in the trajectory of the shot.
  • The client wanted to partner with various providers so that the user can redeem accumulated rewards from various bets.

Our Approach

  • An Android and iOS application was developed to allow users to have an interface in order to view the live games happening around.
  • The application was using RTSP to communicate with the source server and establish a connection between the client and server.
  • Using RTSP throttle, the video streaming issue was solved. The client-side was able to pass the parameters such as codec selection, bit rate, and desired quality to be received.
  • If an end consumer was on a throttled network, they could still view the video being streamed but the quality of the same is low. This helped in decreasing the dropout numbers.
  • The client was able to explore a SAAS offering using the app and partnered with various sports agencies to monitor a player’s performance.
  • AR was used to monitor the trajectory of the ball passed, the speed of the shots, and accuracy in terms of short passes and throughputs. 
  • Sports agencies even used the AR feature to view the placement of the players on the field.

Benefits

  • An Android and iOS application was developed to allow users to have an interface in order to view the live games happening around.
  • The application was using RTSP to communicate with the source server and establish a connection between the client and server.
  • Using RTSP throttle, the video streaming issue was solved. The client-side was able to pass the parameters such as codec selection, bit rate, and desired quality to be received.
  • If an end consumer was on a throttled network, they could still view the video being streamed but the quality of the same is low. This helped in decreasing the dropout numbers.

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