Multi-Platform Content Normalization for Device-Specific Delivery
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Solution Overview
Problem
Existing systems struggle to efficiently distribute and adapt interactive content across diverse client devices with varying input/output capabilities and platforms, leading to inefficient use of computing resources and suboptimal user experiences.
Innovation Solution
A multi-platform content normalization engine that adapts content based on the capabilities of both client devices and platforms, ensuring efficient delivery of enriched content while optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content is distributed to diverse client devices with varying capabilities, then user experience quality improves, but network resource consumption increases
Solution Approach 1:
The system determines the capabilities of each client device and platform combination, then delivers content with the appropriate level of enrichment locally tailored to each recipient. High-capability devices receive enriched content with additional media types and interactive elements, while low-capability devices receive essential content only, optimizing network resource usage while maintaining adaptability.
Solution Approach 2:
Content is segmented into essential components and enhanced components. The adaptation engine separates base content from enriched content, allowing selective delivery based on device capabilities. This segmentation enables the system to provide adaptability without always transmitting the full enriched content set, thereby reducing network resource consumption.
2Adaptability or versatility
If enriched content is delivered to all devices, then user experience quality improves, but computational efficiency decreases
Solution Approach 1:
The system applies partial enrichment by delivering only the necessary level of content enhancement for each device. Rather than providing full enriched content to all devices (excessive action), the adaptation engine delivers exactly what is needed - essential content for basic functionality and selective enriched content for capable devices, thereby improving computational efficiency while maintaining adaptability.
3Adaptability or versatility
If content is optimized for each specific device, then user experience quality improves, but system complexity increases
Solution Approach 1:
The adaptation engine serves multiple functions through a single system: it determines device capabilities, selects appropriate content versions, manages delivery, and handles multiple content formats. This universal approach enables device-specific optimization without proportionally increasing system complexity, as one multi-functional engine handles all adaptation tasks across diverse platforms.
4Adaptability or versatility
If all content types are transmitted to support diverse platforms, then platform compatibility improves, but network bandwidth consumption increases
Solution Approach 1:
The system extracts and transmits only the essential content required for each device, removing unnecessary enriched content types. For low-capability devices, only essential content is transmitted. For high-capability devices, additional content types are extracted and added. This selective extraction approach maintains platform compatibility while reducing overall network bandwidth consumption compared to transmitting all content types to all devices.
Data Source
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AI summary
The present specification provides a content normalization server and method. The specification can have particular application to client devices with augmented or virtual reality hardware that interact with different platforms with metaverse capabilities. Rich experiences are provided on client hardware while making efficient use of available processing, memory and communication resources.