Virtual Reality System for Dynamic User Preference Settings
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Solution Overview
Problem
Current computer systems fail to dynamically update user preference settings based on user behavior, leading to suboptimal performance and increased latency due to reliance on manual updates or periodic queries, which consume processing resources and network bandwidth.
Innovation Solution
A virtual reality system that adjusts user preference settings by analyzing user responses to virtual simulations through biometric data, using a network device and virtual reality device in conjunction with machine learning models to dynamically modify settings without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If periodic queries are sent to users to update preference settings, then user preference settings can be updated, but processing resources and network bandwidth are consumed and latency is introduced
Solution Approach 1:
The system enables self-service by automatically collecting user preference data through biometric sensors during virtual reality interactions. The virtual reality device continuously monitors user physiological responses and behavior patterns, automatically updating preference settings without requiring external queries or manual user input, thus eliminating the resource consumption and latency associated with periodic system-initiated updates
Solution Approach 2:
The system implements continuous feedback loops where biometric data from user interactions with virtual simulations is immediately processed to dynamically adjust preference settings. This real-time feedback mechanism allows the system to adapt to changing user preferences as they occur, eliminating the need for periodic queries and maintaining optimal system performance while continuously improving user experience
2Adaptability or versatility
If manual user input is required for preference settings, then settings can be updated, but the system cannot learn user behavior or dynamically update settings over time
Solution Approach 1:
The system replaces manual mechanical input methods with automated biometric sensing and machine learning algorithms. Instead of requiring users to manually adjust settings through interfaces, the system uses sensors to detect physiological signals (heart rate, eye tracking, facial expressions) and automatically processes this data through AI models to infer user preferences and dynamically adjust settings, thereby achieving adaptive learning without significant operational complexity
Solution Approach 2:
The virtual reality device serves multiple functions simultaneously: it provides the immersive virtual simulation experience while also functioning as a biometric data collection platform. The same hardware components used for virtual reality rendering (cameras, sensors, processors) are leveraged to collect and analyze user physiological responses, eliminating the need for separate dedicated monitoring equipment and reducing overall system complexity while enabling dynamic preference learning
Data Source
AI summary
A device is configured to establish a network connection with a virtual reality device and to identify a user account that is associated with the virtual reality device. The device is further configured to send a virtual simulation survey to the virtual reality device. The virtual simulation survey includes a list of virtual simulations that can be rendered by the virtual reality device. The device is further configured to receive a survey response from the virtual reality device. The survey response identifies one or more virtual simulations from the list of virtual simulations. The device is further configured to determine a cumulative user preference settings value based on the virtual simulations identified in the survey response and to modify user preference settings within the user account based on the cumulative user preference settings value.