Video Session Contextual Feature Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video communication applications lack automated features that can effectively identify and respond to contextual scenarios within sessions, such as unanswered questions or follow-up events, leading to inefficiencies in information dissemination and task management.
Innovation Solution
A processor analyzes application data from video communication sessions using natural language processing and AI models to identify contextual features, such as unanswered questions or noteworthy events, and generates automated communications or actions, like drafting emails or capturing relevant information, to address these scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated features are implemented to identify and respond to contextual scenarios, then productivity and information sharing are improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary processing system that sits between the video communication application and the user interface. This intermediary layer automatically analyzes session data, identifies contextual scenarios, and generates appropriate responses without requiring complex integration throughout the entire application architecture. The intermediary acts as a mediator that simplifies the overall system design while enabling automated features.
Solution Approach 2:
The system implements self-service automation where the video communication application automatically monitors its own session data, identifies contextual scenarios, and generates responses without external intervention. The application serves itself by using its existing data structures and processing capabilities to detect scenarios like unanswered questions or noteworthy events, eliminating the need for complex external monitoring systems.
2Productivity
If automated scenario identification is implemented, then task management is improved, but ease of operation decreases
Solution Approach 1:
The system provides feedback to users by presenting identified contextual scenarios and suggested responses through the existing user interface. Users receive information about detected scenarios (such as unanswered questions or noteworthy events) and can review, modify, or reject automated responses before they are executed. This feedback mechanism maintains user control while enabling automated task management.
Solution Approach 2:
The system performs preliminary analysis of session data to identify contextual scenarios before they require user attention. By proactively detecting scenarios like unanswered questions or important events and presenting them to users in advance, the system improves task management efficiency while allowing users to control the timing and execution of responses at their convenience.
Data Source
AI summary
A processor may receive application data regarding a session on a video communication application. The processor may receive user data regarding one or more participants associated with the session. The processor may analyze application data to identify contextual features of the application data. The processor may identify that a first contextual scenario has occurred.