Live Workout Video Wall With Eligibility-Based Stream Moderation
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Solution Overview
Problem
Maintaining motivation in fitness regimes is challenging due to competing life priorities, and existing exercise systems lack community engagement features to sustain user engagement.
Innovation Solution
A system and method for a virtual wall of live streams during workout sessions, moderated by eligibility criteria, including participant selection based on factors like workout experience, community score, and real-time monitoring for inappropriate content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a wall of live streams is displayed to foster community engagement, then user motivation is enhanced, but system complexity and moderation burden increase
Solution Approach 1:
The system implements automated eligibility checking where participants self-register and the system automatically determines their eligibility based on predefined criteria (workout completion history, community score, etc.), eliminating the need for manual moderation of each participant
Solution Approach 2:
Manual moderation processes are replaced with automated computational systems that evaluate participant eligibility, monitor live streams, and enforce community guidelines through algorithms and AI-based content analysis
2Reliability
If eligibility criteria are applied to select participants, then content quality is maintained, but participant selection complexity increases
Solution Approach 1:
Eligibility criteria are evaluated and participants are pre-screened before they join the live workout session. The system checks workout completion history, community scores, and other metrics in advance, so that only eligible participants are admitted to the live stream wall
Solution Approach 2:
The system uses multiple quantifiable parameters (workout completion count, community score thresholds, recent activity levels) to objectively determine eligibility, transforming subjective quality assessment into measurable parameter-based decisions
3Reliability
If real-time monitoring is implemented to detect inappropriate content, then workout experience quality is maintained, but processing load and system resources increase
Solution Approach 1:
The system uses rapid automated content analysis that quickly scans and evaluates live streams for inappropriate content, passing through the monitoring process efficiently without manual intervention for each frame or segment
Solution Approach 2:
AI-based content analysis tools and automated moderation algorithms serve as intermediaries between the live stream content and human moderators, filtering out obviously inappropriate content automatically and only flagging ambiguous cases for human review
Data Source
AI summary
Disclosed are example embodiments of systems and methods for displaying a workout session having a virtual wall of live streams. The system includes one or more processors and a memory coupled to the one or more processors. The memory has instructions that, when executed, cause the one or more processor to determine whether a plurality of participants are eligible to be presented on a wall of live streams of a live workout session based at least on an eligibility criteria. The memory also has instructions that, when executed, cause the one or more processor to display a video stream of a first participant from the plurality of participants on the wall of live streams based on the determination.