Virtual Store Arrangement in VR Platforms
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Solution Overview
Problem
The increasing abundance of digital content poses challenges for user navigation and interaction, as conventional techniques become unwieldy and difficult to manage, especially with the enhancement of richness through virtualization technologies like augmented and virtual reality.
Innovation Solution
The implementation of virtual environment arrangement and configuration techniques using virtual reality platforms, which employ virtualization, augmented reality, and machine learning to create intuitive and efficient virtual environments that mimic physical stores, allowing users and providers to customize and automate the arrangement of virtual stores and digital content for improved navigation and conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional favoriting techniques are used to manage digital content, then users can locate particular webpages during navigation, but the technique becomes unwieldy and difficult to navigate due to the sheer number of items of interest
Solution Approach 1:
The patent transitions from conventional 2D webpage favoriting to a 3D virtual environment where digital content is displayed as virtual stores along virtual streets. This dimensional change allows users to navigate through spatial arrangements rather than flat lists, improving navigation ease when dealing with large numbers of items.
Solution Approach 2:
The virtual environment segments digital content into organized virtual stores grouped along virtual streets. This segmentation divides the overwhelming number of digital items into manageable, spatially-separated categories, reducing system complexity and improving navigability.
2Adaptability or versatility
If virtualization techniques are used to expand richness in display and user interaction, then user interaction with digital content is enhanced, but navigation through representations of digital content becomes more difficult
Solution Approach 1:
The virtual environment provides dynamic navigation capabilities where users can move freely through 3D space, approach virtual stores from different angles, and interact with content at varying distances. This dynamic spatial interaction maintains navigation ease while enhancing interaction richness through multiple engagement modes.
Solution Approach 2:
The virtual environment acts as an intermediary layer between the user and digital content, providing intuitive spatial metaphors (streets, stores, displays) that simplify navigation while enabling rich interactions. This intermediary maintains ease of operation by using familiar spatial concepts while delivering enhanced versatility.
3Productivity
If machine learning is used to automatically arrange virtual stores, then configuration time is reduced, but computational resources and processing power increase
Solution Approach 1:
Machine learning models perform preliminary analysis of user preferences, browsing patterns, and content characteristics to pre-arrange virtual stores in optimal configurations. This preliminary action automates the configuration process, significantly reducing manual setup time while the computational cost is amortized over multiple user sessions.
Solution Approach 2:
The system uses machine learning to enable self-service automatic arrangement of virtual stores based on user behavior patterns. Once trained, the model autonomously configures environments without requiring extensive computational resources for each individual configuration, reducing ongoing energy consumption.
Data Source
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AI summary
Virtual environment arrangement and configuration techniques are described. In one example, virtualization techniques are employed to generate a virtual environment as implemented via a virtual reality platform by one or more computing devices. The virtual environment includes virtual stores arranged along virtual streets. Virtual digital content is included in the stores, such as to initiate conversion of a good or service represented by the content. Configuration of the virtual environment is based on user, provider, and/or machine learning inputs.