Distributed Set-Top Box Data Processing for Audience Measurement
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Solution Overview
Problem
The existing methods for collecting, storing, and processing viewing usage data are costly and inefficient, requiring expensive centralized systems and relying on probabilistic methods to extrapolate data to larger audiences, which reduces the reliability and value of the data for advertisers and providers.
Innovation Solution
The use of advanced set-top box technology with increased memory and processing capabilities allows raw viewing usage data to be collected and processed locally, with individualized programming instructions enabling more efficient data manipulation and reporting, reducing the need for centralized processing and enhancing data reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a centralized data mining system with large storage and processing capability is used, then data processing capability is improved, but system cost increases
Solution Approach 1:
The patent segments the centralized data mining function into distributed processing units located in individual set-top boxes. Each STB performs local data collection, filtering, and preliminary processing, then transmits only processed results to a simplified centralized system. This segmentation reduces the processing burden and cost at the centralized level while maintaining overall data processing capability.
2Measurement precision
If all raw usage data is transferred to the centralized system, then measurement precision is improved, but data transmission cost and time increase
Solution Approach 1:
The set-top boxes perform preliminary data processing locally by collecting raw usage data, filtering irrelevant information, and pre-processing the data according to specific processing instructions before transmission. This preliminary action at the edge reduces the volume of data that needs to be transferred to the centralized system, thereby reducing transmission time and cost while preserving the precision needed for accurate audience measurement.
3Device complexity
If probabilistic methods are used to extrapolate data to larger audiences, then system cost is reduced, but reliability of data decreases
Solution Approach 1:
Each set-top box autonomously executes specific processing instructions received from the centralized system, performing local data collection, filtering, and processing without requiring constant centralized control or probabilistic extrapolation. This self-service capability at the distributed level enables the system to maintain high data reliability through actual measured data from individual households while keeping system costs lower than a fully centralized approach.
Data Source
AI summary
One or more embodiments of the invention provide a method, apparatus, and article of manufacture for processing viewing usage data in a set-top box. A set-top box (STB) receives, via broadcast, distinct programmable instructions for data collection, data manipulation, and data reporting for viewing usage data. The STB then obtains/collects raw viewing usage data in accordance with the instructions for data collection. Once collected, the STB manipulates the raw viewing usage data to create a report in accordance with the instructions for data manipulation. The report is then transmitted from the set-top box to a centralized data mining system in accordance with the instructions for data reporting.