EPG Timing Prediction for Program Overrun Scheduling
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Solution Overview
Problem
Existing media distribution systems often fail to accurately reflect the end-time of media programs, leading to user frustration when programs overrun their scheduled end-times, and EPGs may become outdated due to infrequent updates, causing confusion and inconvenience.
Innovation Solution
A media system that includes a receiver capable of predicting the actual end-time of a media program by analyzing distribution schedules and event data, allowing it to modify EPG data to reflect the correct end-time and retrieve additional content from alternative sources to ensure seamless program transitions, and generate updated EPGs to provide accurate scheduling information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the EPG is updated frequently to reflect actual program end-times, then the accuracy of scheduling information is improved, but the system complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary actions by predicting program end-times before the actual EPG update cycle. The receiver analyzes distribution schedules and event data in advance to forecast when programs will actually end, allowing the EPG to be pre-updated with accurate timing information rather than waiting for post-program confirmation data.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring actual program distribution against scheduled timelines. When discrepancies are detected (such as programs running longer than scheduled), the system feeds this information back into the EPG generation process to dynamically adjust and update program end-times, ensuring the EPG reflects real-world conditions.
2Measurement precision
If the system predicts program end-times using distribution schedules and event data, then the accuracy of program timing information is improved, but the processing time and computational resources increase
Solution Approach 1:
The system applies partial action by focusing prediction efforts only on programs that are currently airing or about to air, rather than analyzing all programs in the schedule simultaneously. The receiver prioritizes real-time prediction for active programs while using cached or pre-processed data for future programs, reducing overall computational burden while maintaining accuracy for time-critical information.
3Ease of operation
If the receiver modifies EPG data in real-time to reflect program overruns, then the user experience is improved, but the data processing load on the receiver increases
Solution Approach 1:
The system extracts only the essential elements needed for EPG modification - specifically program end-time predictions and scheduled timing data - while leaving more complex analysis and full program metadata processing to external servers or guide data sources. This selective extraction approach allows the receiver to perform real-time EPG updates with minimal processing overhead, focusing computational resources only on the critical timing adjustment function.
Data Source
AI summary
In one aspect, an example system includes a first distributor server to cause transmission of first media associated with first data representing a first state of the first media scheduled to end at a scheduled end-time. The example system includes a receiver to obtain second data representing a second state of a past event corresponding to a subject of the first media, determine a predicted end-time of the first media based on a comparison of the first and second states, and after a determination that the predicted end-time is after at least one of the scheduled end-time of the first media or a scheduled start-time of second media, generate an electronic program guide (EPG) based on the predicted end-time. The example system also includes a second distributor server to cause transmission of a portion of second media to the receiver, the second distributor server different from the first distributor server.