Hybrid Structure Display With Personalized Viewing Regions
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Solution Overview
Problem
Large format displays can be difficult for users to view due to size constraints, and existing technologies struggle to provide personalized content without user specification, especially for users with eye issues or varying viewing distances.
Innovation Solution
A hybrid structure display that integrates a display component with an environmental structure, utilizing sensors and processors to detect user position and identity, allowing for personalized content delivery through subset regions tailored to individual users, including facial recognition and machine learning for content scaling and segmentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If large format displays are used to provide personalized content, then content personalization is improved, but viewing difficulty increases due to size constraints
Solution Approach 1:
The display is divided into multiple subset regions, each tailored to a specific user. The processor segments the display content based on detected user positions and identities, creating personalized viewing zones that make the large format display accessible and comfortable for multiple users simultaneously.
Solution Approach 2:
Different portions of the display are optimized for different users based on their viewing characteristics. Each subset region is customized with content scaling and positioning appropriate to the specific user's location, eye level, and viewing distance, making the local viewing experience comfortable despite the overall large size.
2Adaptability or versatility
If sensors and processors are added for user detection and personalization, then content personalization is improved, but device complexity increases
Solution Approach 1:
The sensor system and processor are designed to perform multiple functions: detecting user position, identifying users through facial recognition, determining eye levels, and scaling content. This multi-functional approach consolidates what could be separate complex systems into an integrated solution that achieves personalization through a unified detection and control architecture.
3Measurement precision
If facial recognition and machine learning are implemented, then user identification accuracy is improved, but processing time increases
Solution Approach 1:
The system performs facial recognition and user identification in advance before content delivery begins. By pre-identifying users and their characteristics when they approach the display, the system prepares personalized subset regions ahead of time, reducing the perceived processing delay during actual content viewing.
Data Source
AI summary
In some examples, an apparatus includes a hybrid structure display including a display component and an environmental structure. In some examples, the apparatus includes a sensor to detect positional information corresponding to a user. In some examples, the apparatus may include a processor to determine a subset region of the hybrid structure display based on the positional information. In some examples, the processor is to cause the hybrid structure display to display a channel of content in the subset region.