Predictive Reconnection Model for Online Meeting Continuity
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Solution Overview
Problem
Current online meeting platforms lack the ability to predict and notify participants about the reconnection time of a disconnected attendee, leading to uncertainty and wasted time when a key participant goes offline.
Innovation Solution
A method that collects historical disconnection data to construct a predictive model, which then predicts the reconnection time of a participant and notifies others when they are expected to return, using a computer program product and system that collects disconnection information and constructs a predictive model to guide meeting participants with real-time reconnection span recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If online meeting platforms monitor participant connectivity status, then meeting disruption detection is improved, but the ability to predict and guide reconnection is insufficient
Solution Approach 1:
The system performs preliminary actions by collecting disconnection information and constructing predictive models in advance, before actual reconnection events occur. This allows the system to predict reconnection times proactively rather than reactively, providing participants with advance notice of when disconnected attendees are expected to return.
Solution Approach 2:
The system implements feedback by continuously monitoring connectivity status, analyzing disconnection patterns, and providing predictive reconnection information back to meeting participants. This closed-loop feedback mechanism transforms raw connectivity data into actionable insights that guide meeting flow and participant expectations.
2Reliability
If the meeting pauses to wait for the moderator to return, then reconnection completeness is improved, but meeting time efficiency deteriorates
Solution Approach 1:
The system applies dynamics by making the meeting flow adaptive rather than static. Instead of rigidly pausing or continuing, the system dynamically adjusts meeting progression based on real-time predictions of participant reconnection, allowing the meeting to proceed optimally while maintaining completeness.
Solution Approach 2:
The system changes the parameter of meeting state from binary (paused/continued) to a spectrum of possibilities based on predicted reconnection timing. This allows flexible decision-making about whether to pause, continue, or adjust the agenda based on quantitative predictions rather than qualitative judgments.
3Device complexity
If no prediction system is implemented, then system complexity is reduced, but participant uncertainty increases
Solution Approach 1:
The system practices self-service by automatically collecting data, constructing predictive models, and providing reconnection information without requiring manual intervention from meeting hosts or participants. The platform serves itself by generating actionable insights from its own connectivity monitoring data.
Solution Approach 2:
The predictive model acts as an intermediary between raw connectivity data and participant decision-making. Rather than presenting raw data or requiring complex analysis, the intermediary model translates connectivity patterns into clear, actionable reconnection predictions that participants can easily understand and act upon.
Data Source
AI summary
A computer-implemented method for automatically recommending an online meeting reconnection time for one or more online meeting participants that are disconnected. The method collects disconnection information for one or more online meeting participants over time as historical data. The method constructs a predictive model for the one or more online meeting participants based on the historical data and predicts a reconnection time for the one or more online meeting participants based on the predictive model. The method notifies the one or more online meeting participants when a disconnected participant is expected to return online and updates the online meeting agenda if the disconnected participant's reconnection time exceeds a predefined threshold.