Metadata-Based Data Stream Filtering for Location and Temporal Synchronization
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Solution Overview
Problem
Existing data streaming technologies lack effective methods for filtering data streams based on metadata comparisons with client data, particularly in applications requiring location-based and temporal data synchronization, which is crucial for real-time video and audio streaming scenarios.
Innovation Solution
A computer-implemented method that filters data streams by comparing metadata encoded in the streams with client data, determining whether the comparison meets specific conditions for frame-by-frame filtering of video and audio streams, ensuring that only relevant data is provided to clients based on location and temporal criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data stream filtering is performed without metadata comparison, then bandwidth consumption is reduced, but data relevance and accuracy deteriorate
Solution Approach 1:
The system performs preliminary filtering by comparing metadata (such as location data, temporal data, and other attributes) against client data before transmitting the actual data stream content. This preliminary action identifies and filters out irrelevant data portions based on predefined conditions, ensuring that only relevant data is transmitted, thus improving data relevance while optimizing bandwidth consumption.
2Measurement precision
If frame-by-frame filtering is performed on video streams, then data accuracy is improved, but processing time increases
Solution Approach 1:
The video stream is segmented into individual frames, and metadata comparison is performed on each frame independently. This segmentation allows the system to apply filtering criteria selectively to specific frames that meet certain conditions (such as containing relevant location or temporal data), rather than processing the entire stream uniformly, thus improving data accuracy while reducing overall processing time.
Solution Approach 2:
Instead of performing exhaustive filtering on every single frame, the system applies partial filtering by comparing metadata and applying conditions only when necessary. The filtering action is excessive in the sense that it checks all frames, but the actual filtering output is partial, only affecting frames that meet the predefined conditions, thereby balancing accuracy with processing efficiency.
3Adaptability or versatility
If metadata encoding is added to data streams, then filtering capability is improved, but device complexity increases
Solution Approach 1:
The metadata encoding scheme is designed to be universal and multi-functional, supporting multiple filtering criteria (location-based filtering, temporal filtering, and other attribute-based filtering) within a single standardized metadata structure. This universal approach allows the same metadata framework to serve multiple filtering purposes, improving filtering capability while avoiding the need for separate complex systems for each filtering type.
Data Source
AI summary
A method, computer program product, and computing system device for receiving a data stream encoded with metadata. Client data may also be received. At least a portion of the data stream may be filtered based upon, at least in part, a comparison of the metadata encoded into the video stream and the client data.