HLS Stream Monitoring with SCTE-35 Marker Tracking
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Solution Overview
Problem
Video streaming platforms face challenges in accurately managing and ensuring advertisement durations align with planned durations due to stream instability and irregularities, affecting user experience and advertiser compliance.
Innovation Solution
A system and method for monitoring and tracking SCTE-35 markers in HLS and MPEG-DASH video streams, utilizing a parsing module, marker identification module, duration computation module, alert generation module, communication module, segment manager, and state management module to accurately determine cue-in and cue-out times and manage ad durations, even with evolving SCTE-35 standards and complex segment URIs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If SCTE-35 markers are used to signal advertisement segments in video streams, then advertisement insertion can be automated and standardized, but stream instability and irregularities cause the actual ad duration to mismatch the planned duration
Solution Approach 1:
The system continuously monitors actual ad duration by detecting cue-out and cue-in markers in the video stream, compares the measured duration against the planned duration from SCTE-35 markers, and generates alerts when mismatches exceed a threshold. This feedback mechanism enables real-time detection and reporting of duration discrepancies, allowing for automated adjustment or manual intervention to ensure ad delivery compliance.
Solution Approach 2:
The patent replaces manual ad duration monitoring with an automated system that uses software modules to parse stream data, detect markers, compute durations, and generate alerts. This substitution of mechanical/manual processes with automated information processing resolves the contradiction by maintaining standardized marker-based insertion while achieving precise measurement through computational analysis.
2Measurement precision
If the system monitors actual ad duration by detecting cue-out and cue-in markers, then measurement precision of ad duration is improved, but device complexity increases due to multiple modules required for parsing, detection, computation, and alert generation
Solution Approach 1:
The monitoring system is divided into distinct functional modules: a parsing module to extract stream data, a marker identification module to detect cue-out and cue-in markers, a duration computation module to calculate ad duration, and an alert generation module to report mismatches. This segmentation allows each module to perform its specific function independently, making the complex system modular and easier to maintain while achieving precise measurement through coordinated operation.
3Reliability
If the system compares measured ad duration with planned duration to ensure compliance, then advertiser compliance is improved, but loss of time increases due to real-time monitoring and alert generation requirements
Solution Approach 1:
The system operates continuously throughout the video stream, constantly monitoring for SCTE-35 markers and computing ad durations in real-time. This continuous monitoring ensures that compliance can be verified as ads are delivered, without requiring post-processing or delayed analysis. The system maintains readiness to detect and report any duration mismatches immediately when they occur, ensuring timely compliance verification while minimizing time loss through efficient real-time processing.
Data Source
AI summary
The invention provides a system and method for monitoring adaptive streaming media, including but not limited to HTTP Live Streaming (HLS) and Dynamic Adaptive Streaming over HTTP (MPEG-DASH), and tracking SCTE-35 markers. The system parses a media playlist, identifies cue-in and cue-out markers, computes and compares the measured and expected durations of ad blocks, generates alerts for mismatches, and communicates findings. This system is capable of accurately determining the cue-in and cue-out times of advertisements in media streams. The invention enhances the accuracy of ad placement, ensuring robustness, adaptability, and effectiveness of advertising campaigns in streaming media.