Client Device Pre-processing for Scalable Audience Measurement
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Solution Overview
Problem
Existing Audience Measurement Systems (AMS) for TV advertisements face challenges in handling large volumes of data, leading to impracticality due to limitations in set-top-box return path bandwidth, data retrieval speed, CPU processing costs, and report generation time, making it difficult to accurately measure viewership across a large number of ad units and user records within a reasonable budget.
Innovation Solution
The solution involves processing event data on a client device to generate viewership reports in real-time, reducing upstream traffic and processing power, and utilizing a distributed computing system with tiers for cost-effective data processing, allowing for accurate and efficient collection and analysis of viewership data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If centralized data processing is used to collect and process all viewer events, then comprehensive viewership measurement is achieved, but processing time and computational cost become impractically long
Solution Approach 1:
The patent applies preliminary action by processing event data locally at the set-top box before transmission to the central server. The set-top box pre-processes viewer events, filters relevant information, and prepares condensed data structures that reduce the processing burden on central systems, thereby significantly reducing overall report generation time while maintaining measurement accuracy
Solution Approach 2:
The patent segments the data processing function across multiple levels: local processing at set-top boxes, regional aggregation at intermediate servers, and central processing at the main server. This segmentation distributes the computational load and enables parallel processing of viewership data from different regions, dramatically reducing the time required to generate comprehensive reports
2Quantity of substance
If all event data is transmitted to central storage, then complete data availability is achieved, but bandwidth requirements and data retrieval speed become insufficient
Solution Approach 1:
The patent extracts and filters only the essential information from raw event data at the set-top box level before transmission. By extracting only relevant viewer events and consolidating them into compact data structures, the system reduces the volume of data transmitted over the network, thereby improving data retrieval speed and reducing bandwidth requirements while maintaining complete data availability for analysis
3Measurement precision
If comprehensive data processing is performed, then accurate viewership reports are generated, but CPU processing cost becomes prohibitively high
Solution Approach 1:
The patent applies preliminary action by performing data processing and filtering operations at the set-top box before transmission to the central server. This pre-processing reduces the volume and complexity of data that requires expensive central CPU processing, thereby maintaining report accuracy while significantly reducing overall computational cost
Solution Approach 2:
The patent implements local quality by enabling set-top boxes to perform intelligent filtering and processing of viewer events based on local conditions and requirements. Each set-top box processes data according to its specific context, generating optimized data structures that reduce the processing burden on central systems while maintaining the quality and accuracy of viewership measurement
Data Source
AI summary
Methods of reporting Audience Measurement System (AMS) viewership events on a client device and systems implementing the method are disclosed. The method comprises the steps of receiving at least one event message on a client device, wherein each event message is a data signal indicating an occurrence of an event, processing the at least one event message on the client device to create an AMS viewership report, and transmitting the AMS viewership report.