Channel Prediction Buffering for Faster TV Channel Changes
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Solution Overview
Problem
Existing channel change methods result in delays due to the need to load program content after switching channels, leading to a poor user experience.
Innovation Solution
A channel prediction method that selects candidate channels based on user behavior and preferences, storing them in a prediction database, and loading program content in advance to speed up channel changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If program content is loaded after channel change, then memory is used efficiently, but channel change time increases causing poor user experience
Solution Approach 1:
The system performs preliminary actions by predicting the next channel the user will switch to and pre-loading its program content into memory before the actual channel change occurs. This eliminates the loading delay during channel switching, directly reducing channel change time while managing memory through intelligent pre-allocation based on prediction algorithms.
2Productivity
If multiple channels are pre-loaded into memory, then channel change speed increases, but memory usage increases
Solution Approach 1:
Instead of pre-loading all possible channels or using excessive memory, the system applies partial action by predicting and pre-loading only the most likely next channel(s) based on user behavior patterns. This selective approach achieves fast channel switching while maintaining efficient memory utilization, avoiding the waste of pre-loading unnecessary channels.
3Ease of operation
If channel prediction is implemented, then user experience improves, but system complexity increases
Solution Approach 1:
The prediction system operates autonomously by automatically analyzing user channel switching patterns and behavior without requiring manual input or configuration. The system self-adjusts prediction algorithms based on observed usage, eliminating the need for complex user setup while improving ease of operation. The complexity is confined to the background prediction engine rather than the user interface.
Data Source
AI summary
A channel prediction method applied to channel change includes: selecting multiple candidate prediction channels from multiple channels in a channel database, and storing the multiple candidate prediction channels into a prediction database; comparing the multiple candidate prediction channels with a channel selected by a user to generate a comparison result; and selecting multiple prediction channels from the multiple candidate prediction channels in the prediction database according to the comparison result, and storing the multiple prediction channels into a channel buffer.