Active Copresence Detection for Mobile Interaction Engagement
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Solution Overview
Problem
The increasing pervasiveness of mobile communication is interfering with users' interactions with present individuals, as users often engage in secondary interactions with non-present individuals during primary interactions, leading to reduced engagement and productivity.
Innovation Solution
A system that determines the degree of active copresence by calculating the difference between primary and secondary interaction times, providing users with a score that represents their level of engagement during interactions, allowing for prioritization of interactions and automation of interrupt settings based on this score.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If mobile communication is made pervasive and accessible anytime anywhere, then users can be accessible to non-present individuals via various communication channels, but user engagement in primary interactions with present individuals deteriorates
Solution Approach 1:
The system implements feedback by continuously monitoring interaction quality scores and providing real-time notifications to users about their engagement levels. The processor calculates quality scores based on multiple parameters (response time, conversation depth, attention level) and feeds this information back to users through the interface, enabling them to adjust their behavior and improve engagement in primary interactions while maintaining accessibility to non-present individuals.
Solution Approach 2:
The system dynamically adjusts interaction management based on real-time conditions. The processor monitors the current state of interactions and adapts the quality score calculations and notifications accordingly. The interface dynamically presents relevant information and suggestions to users based on their current engagement patterns, allowing the system to respond flexibly to changing interaction scenarios.
2Adaptability or versatility
If users engage in secondary interactions during primary interactions, then accessibility to non-present individuals is maintained, but the quality and depth of primary interactions deteriorates
Solution Approach 1:
The system segments the overall interaction quality into distinct measurable components. The processor divides the quality assessment into separate dimensions including response time, conversation depth, attention level, and interruption frequency. This segmentation allows precise measurement of how secondary interactions affect primary interaction quality without conflating different aspects of engagement.
Solution Approach 2:
The system changes parameters to quantify interaction quality objectively. The processor transforms subjective engagement concepts into measurable parameters such as response time (temporal parameter), conversation depth (structural parameter), and attention level (cognitive parameter). These parameter changes enable precise measurement and comparison of interaction quality across different scenarios.
3Adaptability or versatility
If users are constantly accessible via mobile communication, then communication availability increases, but loss of time and attention in primary interactions increases
Solution Approach 1:
The system takes preliminary action by providing users with advance information about their interaction quality patterns and potential time loss. The processor analyzes historical data and predicts future engagement scenarios, then presents this information to users before critical decisions are made. This allows users to proactively manage their time and attention allocation across different interaction types.
Solution Approach 2:
The system enables self-service by empowering users to autonomously manage their own engagement quality. The interface presents quality scores and time loss metrics directly to users, allowing them to self-regulate their communication behavior without external intervention. Users can independently adjust their accessibility settings and interaction priorities based on the system's feedback.
Data Source
AI summary
A system is described for determining the active copresence of users during interactions. The system may include a processor, a memory, and an interface. The memory may store a degree of active copresence. The interface may communicate with a user. The processor may identify a primary interaction of the user. The processor may determine whether the user engages in a secondary interaction while the user is engaged in the primary interaction. The processor may determine the degree of active copresence of the user during the primary interaction based on a quality score of the primary interaction and a quality score of the secondary interaction. The degree of active copresence may represent the level of engagement of the user during the primary interaction. The processor may provide the degree of active copresence to the user via the interface.


