Personalized Media Playlist Engine for Bandwidth Optimization
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Solution Overview
Problem
Current media content streaming technologies waste bandwidth and user resources due to the transmission of unwatched videos, leading to increased consumer costs and time wastage, as users are often presented with generic and repetitive playlists that do not align with their preferences.
Innovation Solution
A rule-based, randomized, and individualized media content management system that uses AI and machine learning to create unique playlists based on user preferences, viewing history, and real-time feedback, optimizing content selection and distribution to minimize unnecessary bandwidth consumption and resource usage while providing a fresh and relevant viewing experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed generic playlist format is used for media content streaming, then the system complexity is reduced and ease of operation is improved, but bandwidth waste increases and user engagement decreases
Solution Approach 1:
The patent implements dynamic playlist generation that adapts to user preferences, viewing history, and real-time feedback. Instead of static generic playlists, the system continuously adjusts content selection and ordering based on user behavior patterns, making the playlist dynamic and personalized while maintaining operational simplicity through automated algorithms
Solution Approach 2:
The system changes multiple parameters including content selection criteria, playlist ordering, and recommendation algorithms based on user feedback and viewing patterns. By adjusting these parameters dynamically, the system reduces bandwidth waste while maintaining ease of operation through automated parameter optimization
2Adaptability or versatility
If numerous videos are transmitted to users in a sequential playlist format, then content variety is increased and adaptability is improved, but bandwidth consumption increases and user time is wasted
Solution Approach 1:
The system performs preliminary actions by pre-analyzing user preferences, viewing history, and engagement patterns before generating the playlist. This advance preparation allows the system to curate highly relevant content that matches user interests, reducing the time users spend scrolling through irrelevant videos while maintaining content variety
Solution Approach 2:
The system implements feedback loops that monitor user engagement metrics such as watch time, skips, and interactions. This real-time feedback enables the system to adjust content selection and playlist ordering dynamically, ensuring users receive varied content that is continuously optimized for their preferences, thereby reducing time waste while maintaining adaptability
3Device complexity
If content presentation devices receive and store unwanted video content, then the device's resource utilization is simplified, but memory usage increases and processing efficiency decreases
Solution Approach 1:
The patent extracts and transmits only the essential and relevant video content to the user's device based on personalized algorithms and engagement prediction. By removing unnecessary content from the transmission stream, the system reduces memory usage and processing requirements while maintaining simplified device architecture through selective content delivery
Data Source
AI summary
A system and method that provides a rule based randomized media content management system. The system includes a database that stores media content that is associated with category metadata that identifies content of the media content with corresponding categories. Moreover, a programming rules engine generates a list of approved media content based on business rules and a predictive rules engine generates media content selection characteristics based on media display device data and media consumption data associated with the viewer. Furthermore, a media content playlist engine is provided that generates a media content playlist by applying the generated media content selection characteristics to the list of approved media content to select media content, such that the resource consumption by the media display device is minimized by selecting media content that is targeted to the viewer of the media display device according to one or more business rules.