Digital Content Spatial Replacement for Audience Adaptation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current content delivery systems fail to adapt and alter digital content in real-time based on audience interests and preferences during playback, limiting the ability to enhance the audience experience beyond minor supplements like closed captioning and ad placement.
Innovation Solution
A digital content delivery method that selects spatial portions of base content for replacement with alternative objects, using audience data collection, processing, and prediction engines to determine likely audience interests and adapt content dynamically, allowing for real-time alterations based on environmental, behavioral, and static data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content is delivered in its original compiled form without alteration, then content integrity and simplicity are maintained, but the ability to adapt content to audience interests is lost
Solution Approach 1:
The content stream is divided into discrete replaceable segments or objects that can be individually targeted for replacement. This allows the system to alter only specific portions of content based on audience interests while leaving the rest intact, thereby achieving adaptability without requiring complete content reprocessing.
Solution Approach 2:
Alternative content objects are prepared and stored in advance before the audience experience begins. When adaptation is needed, these pre-prepared alternatives are simply swapped in rather than generated in real-time, reducing the computational complexity required during content delivery.
2Adaptability or versatility
If content is altered in real-time based on audience data, then audience engagement and personalization are enhanced, but processing time and computational resources increase
Solution Approach 1:
The system processes and stores multiple alternative content objects in advance, so that during real-time delivery, it only needs to select from pre-processed options based on audience data. This eliminates the need for complex real-time content generation while still achieving personalized adaptation.
Solution Approach 2:
The system uses pre-rendered alternative content objects that are copies or variations of the original content, created beforehand. During delivery, these copies are substituted into the content stream without requiring real-time processing of the original content, thus minimizing processing time.
3Adaptability or versatility
If multiple alternative content objects are prepared for replacement, then content personalization options increase, but data storage requirements and system complexity increase
Solution Approach 1:
The system stores alternative content objects organized by specific replaceable locations or segments within the content stream. Each alternative object is tagged with metadata indicating where it can be inserted, allowing the system to retrieve only the relevant alternatives needed for a given audience rather than storing all possible variations.
Solution Approach 2:
The alternative content objects are designed with universal structures and metadata schemas that allow them to be used across multiple different contexts and audience types. A single alternative object can serve multiple replacement locations or different audience segments, reducing the total number of unique objects that need to be stored.
Data Source
AI summary
A selected spatial portion of digital base content is selected, and one or more alternative content objects is selected to replace the spatial portion. The spatial portion may comprise less than a full frame of the base content, although it may span multiple frames, and may move within the successive frames. The replacement may occur before or after distribution of the content. The selections may be made based upon knowledge of general or specific audiences. The selections may facilitate bandwidth or processing, allow for product placements, or generally enhance the audience experience.