Selective Data Stream Modification for Entity-Specific Content Control

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Solution Overview

Problem

Conventional livestreaming content control techniques are imprecise, unreliable, and inconsistent, leading to undesirable content remaining in data streams and reducing quality, while failing to provide customized control based on specific entities or user devices.

Innovation Solution

A system that utilizes generative artificial intelligence to selectively modify data streams based on entity-specific content parameters, determining a ruling set of parameters to ensure precise, reliable, and consistent content control, including or excluding specified content as needed, and reducing bandwidth usage through condensed representations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional livestreaming content control techniques are used, then the system is simple to operate, but content control precision and reliability deteriorate

Engineering Contradiction:

Improvecontent control precisionVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments content control by creating separate parameter sets for different entities (sponsors, advertisers, recipients) and different content types. Each entity receives customized content control parameters, allowing precise control without requiring a monolithic complex system. The segmentation enables modular processing of content parameters.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically determines a ruling set of content parameters based on the specific data stream, entities involved, and context. Rather than using static conventional techniques, the system adapts the content control parameters in real-time, selecting from multiple entity-specific parameter sets to achieve reliable and precise control.

Inventive Principle:

Principle #15Dynamics

2Reliability

If conventional content control techniques are used, then bandwidth usage is lower, but content control reliability deteriorates

Engineering Contradiction:

Improvecontent control reliabilityVSAvoidbandwidth usage

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system performs preliminary determination of the ruling content parameter set before processing the data stream. By pre-establishing the appropriate entity-specific parameters and conditions, the system ensures reliable content control from the outset, avoiding the need for retransmissions or corrections that would increase bandwidth usage.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system changes content parameters based on the specific entity and data stream context. By dynamically adjusting parameters such as content thresholds, filtering criteria, and modification rules, the system achieves reliable content control optimized for each scenario, preventing unnecessary data transmission and reducing bandwidth consumption.

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If conventional content control techniques are used, then processing speed is faster, but adaptability to different entities deteriorates

Engineering Contradiction:

Improveentity-specific customizationVSAvoidprocessing speed

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system performs preliminary identification of entities and determination of applicable parameter sets before data stream processing. This advance preparation enables the system to apply the correct entity-specific content parameters without slowing down the main processing pipeline, thus maintaining high productivity while achieving full adaptability.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates a universal framework that handles multiple entities (sponsors, advertisers, recipients) through a common architecture. By designing the system to universally process different entity types using their respective parameter sets, it achieves both high adaptability and efficient processing without requiring separate specialized systems for each entity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Measurement precision

If data streams are modified to satisfy content parameters, then content control precision improves, but data stream quality may deteriorate

Engineering Contradiction:

Improvecontent control precisionVSAvoiddata stream quality

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The system applies content parameter modifications locally and selectively rather than globally. By identifying specific portions of the data stream that require modification based on entity-specific parameters, the system maintains high content control precision while preserving the overall quality and integrity of the data stream, minimizing information loss.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS12556753B2Selectively modifying a data stream based on content parameters

Publication Date: 2026.02.17 CAPITAL ONE SERVICES LLC

AI summary

In some implementations, a system may receive a data stream input. The system may identify one or more sets of content parameters associated with the data stream input, each set of content parameters being associated with a different entity. The system may determine a ruling set of content parameters based on the one or more sets of content parameters. The system may selectively modify the data stream input based on a determination of whether a condition indicated by the ruling set of content parameters is satisfied in the data stream input. The system may provide a data stream output resulting from the selective modification of the data stream input.