Adaptive Media Playback System for Destination-Based Content Assembly
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Solution Overview
Problem
Current media playback systems fail to adapt content to users' anticipated destinations, relying on general geographic location and ignoring individual user interests, resulting in non-tailored and non-customized media experiences.
Innovation Solution
A system that determines user destinations, collects relevant media content, assembles it into a program, and outputs it dynamically, using an adaptation engine to select and order media segments based on user profiles and changing travel paths, ensuring contextual relevance and adaptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If general geographic location is used to target content, then content delivery coverage is improved, but content relevance to individual users deteriorates
Solution Approach 1:
The patent segments the audience from a general geographic location into individual user profiles with specific interests, preferences, and destination information. This allows the system to deliver content that is both geographically relevant and individually customized, resolving the contradiction between broad coverage and personalized relevance.
Solution Approach 2:
The system performs preliminary actions by collecting user profile information, destination data, and media content in advance before the actual media playback. This pre-processing enables the adaptation engine to quickly generate personalized content assemblies based on predetermined user characteristics and destination information.
2Ease of manufacture
If linear prerecorded tours are used, then content delivery simplicity is improved, but user flexibility in browsing deteriorates
Solution Approach 1:
The patent transforms the static, linear prerecorded tour into a dynamic content assembly process. The adaptation engine dynamically selects and assembles media segments based on user profiles and destination information, allowing the content to adapt to user preferences and non-linear browsing patterns while maintaining delivery simplicity through automated processing.
Solution Approach 2:
The system changes the parameter of content delivery from fixed linear sequences to flexible parameter-based selection. Media segments are selected based on multiple parameters including user interests, destination relevance, and travel path information, enabling both simplified automated delivery and user flexibility in content exploration.
3Adaptability or versatility
If media content is assembled dynamically based on user profiles and destinations, then content relevance is improved, but system complexity deteriorates
Solution Approach 1:
The system implements self-service by using the adaptation engine to automatically collect user profile information, determine destinations, select relevant media content, and assemble personalized programs without manual intervention. This automation handles the complexity internally while presenting a simple interface to users, resolving the contradiction between high content relevance and system complexity.
4Adaptability or versatility
If destination-specific media content is collected and assembled, then media playback adaptability is improved, but processing time deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-collecting user profile data, destination information, and media content segments before the actual playback session. The adaptation engine prepares content assemblies in advance based on predetermined criteria, significantly reducing the processing time required during actual media playback while maintaining high adaptability.
Data Source
AI summary
Disclosed herein are systems, methods, and computer readable-media for adaptive media playback based on destination. The method for adaptive media playback comprises determining one or more destinations, collecting media content that is relevant to or describes the one or more destinations, assembling the media content into a program, and outputting the program. In various embodiments, media content may be advertising, consumer-generated, based on real-time events, based on a schedule, or assembled to fit within an estimated available time. Media content may be assembled using an adaptation engine that selects a plurality of media segments that fit in the estimated available time, orders the plurality of media segments, alters at least one of the plurality of media segments to fit the estimated available time, if necessary, and creates a playlist of selected media content containing the plurality of media segments.