Adaptive Computing Device Play Personality Analysis
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Solution Overview
Problem
Current technologies lack a systematic approach to translate the scientific understanding of play into practical applications that can benefit individuals and businesses, despite a robust literature on play's role in human development and emotions.
Innovation Solution
A system and methodology for determining a person's play personality, narrating or graphically representing play types and patterns, identifying intrinsic motivators, storing and updating a play profile, and performing actions to ensure play needs are met, including assessing and identifying play deprivation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a computing device provides standardized operational modes, then ease of operation is improved, but adaptability to individual user needs deteriorates
Solution Approach 1:
The system dynamically adjusts operational parameters by transitioning from static, pre-defined modes to adaptive modes that continuously modify behavior based on real-time analysis of user biometric data and contextual information. The computing device evolves its operational characteristics to match the user's current state, resolving the contradiction between standardized operation and individual adaptability.
Solution Approach 2:
The system implements closed-loop feedback by monitoring user responses (biometric data, interaction patterns) and using this information to automatically adjust operational parameters. This feedback mechanism enables the device to learn from user behavior and adapt its behavior accordingly, maintaining ease of operation while achieving personalized adaptability through data-driven adjustments.
2Adaptability or versatility
If operational parameters are manually adjusted, then adaptability is improved, but loss of time increases
Solution Approach 1:
The system performs self-adjustment of operational parameters by automatically analyzing user biometric data and contextual information to determine optimal settings. This eliminates the need for manual intervention, allowing the device to adapt to user needs autonomously and instantly, thereby achieving adaptability without time loss.
Solution Approach 2:
The system proactively adjusts operational parameters before the user explicitly requests changes by continuously monitoring biometric data and predicting upcoming needs. This preliminary adaptation ensures the device is already optimized when the user interacts with it, eliminating the time that would otherwise be spent on manual adjustment.
3Reliability
If play activities are encouraged, then emotional development is improved, but loss of time for productive work increases
Solution Approach 1:
The system dynamically balances play and work activities by adjusting the proportion and timing of play interventions based on real-time assessment of user emotional state, task requirements, and productivity metrics. This dynamic allocation ensures play occurs at optimal moments for emotional benefit while minimizing disruption to productive work flow.
Solution Approach 2:
The system integrates play activities continuously rather than as discrete interruptions, weaving brief playful interactions throughout the workday in a continuous manner. This approach maintains emotional development benefits while ensuring productive work continues without significant breaks, as play is embedded within rather than separate from the work flow.
Data Source
AI summary
Techniques are described herein for automatically determining play states, intrinsic motivators, play types/patterns and a play personality of a user/subject. Play personalities develop from activation of play states, and vary individually and are expressed in a variety of play type/patterns. These states, personalities, patterns and associated intrinsic motivations may be automatically determined by computing devices based on that user/subject's information, behaviors and biometric data. The play personality may be additionally used as the means for identifying and integrating intrinsic motivators into player-centric design which can alter and personalize user/subject/player engagement, experience and outcomes.