Dynamic Media Data Management for Aircraft Entertainment
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Solution Overview
Problem
Airlines face high costs due to charging for the entire multimedia content set loaded on aircraft, including less frequently viewed content, as they must pay based on the size and duration of the content set, regardless of usage, which does not align with passenger viewing habits.
Innovation Solution
A dynamic media management system that collects user viewing habits to rank and prioritize media content items, allowing for adaptive resizing of media data sets based on anticipated passenger demand, focusing on frequently requested content for preloading, thereby reducing unnecessary content storage and associated costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the entire multimedia content set is loaded onto the aircraft, then passengers have access to a wide variety of content, but airlines incur high costs for storing and maintaining content that is not frequently viewed
Solution Approach 1:
The content library is segmented into frequently viewed and infrequently viewed content based on usage analytics. Only the frequently viewed segment is loaded onto the aircraft, while the infrequently viewed segment remains on ground servers. This segmentation allows airlines to maintain content variety for passengers while significantly reducing storage costs by not loading the entire content set.
Solution Approach 2:
The system dynamically adjusts the content loaded onto aircraft based on real-time and historical usage data. Content rankings are continuously updated, and the content set is dynamically resized to include only the top-ranked frequently viewed content for each specific flight, optimizing the balance between content variety and storage cost.
2Quantity of substance
If more multimedia content is stored onboard, then passenger entertainment options increase, but the storage space and associated costs increase proportionally
Solution Approach 1:
Instead of loading the complete content library, the system applies partial action by loading only the necessary portion - specifically, the top-ranked frequently viewed content based on usage analytics. This partial loading approach provides sufficient entertainment options for passengers while avoiding the excessive storage costs of loading the entire content set.
Solution Approach 2:
The system changes the parameter of content quantity by dynamically adjusting the size of the content set based on usage metrics. Content is ranked and filtered according to viewing frequency, and the content volume loaded onto each aircraft is optimized to match actual passenger demand patterns, reducing storage costs while maintaining adequate content variety.
3Ease of operation
If content is preloaded onto aircraft during layovers, then content is available for passengers, but airlines pay for content that may not be viewed during the flight
Solution Approach 1:
The system performs preliminary action by preloading content onto aircraft before flights, but intelligently selects only the frequently viewed content for preloading based on usage analytics from previous flights. This preliminary action ensures content availability for passengers while avoiding the waste of preloading content that will not be viewed, thereby reducing content costs.
Solution Approach 2:
The system uses feedback from usage analytics and passenger viewing habits to determine which content should be preloaded. By analyzing what content was actually viewed on previous flights, the system adjusts the content selection for future preloading, ensuring that only relevant, frequently viewed content is loaded, thus avoiding payment for unused content.
Data Source
AI summary
A system for managing media content data sets loaded onto a content server has a media content repository storing media content data items. A usage data aggregator retrieves usage log data from each passenger terminal device of the vehicle entertainment system. A load set generator builds a ranked media content data set based upon prioritization scores assigned to each of the media content data items with adaptive inferences from the usage log data. The prioritization scores are correlated with trip factors established for a subsequent vehicle trip for which the ranked media content data set is being built. A content retriever transfers the one or more media content data items specified in the ranked media content data from the media content repository.