Mobile Device Application Usage Classification in Vehicles
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Solution Overview
Problem
There is a challenge in determining the usage patterns of mobile device applications versus in-vehicle infotainment applications in connected cars, as existing methods struggle to differentiate between the two when both are available to the user, affecting resource allocation for media presenting software providers and car manufacturers.
Innovation Solution
The solution involves using Service Set Identifier (SSID) detection and impression logging to classify mobile device usage in connected cars, allowing audience measurement entities to differentiate between mobile device application usage and in-vehicle infotainment application usage by detecting SSIDs and correlating this information with application usage data, enabling the calculation of usage ratios and patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SSID detection and impression logging are implemented to differentiate mobile device and in-vehicle application usage, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces an audience measurement entity as an intermediary system that collects SSID detection data and application usage information from mobile devices and in-vehicle infotainment systems. This intermediary processes the data to differentiate usage patterns without requiring complex differentiation logic within each device itself, thus improving measurement precision while managing overall system complexity through centralized processing
Solution Approach 2:
The patent segments the usage data collection process into distinct components: SSID detection data from mobile devices, application usage data from both mobile and in-vehicle systems, and processing operations at the audience measurement entity. This segmentation allows each component to be optimized independently, improving measurement precision for application usage differentiation while managing complexity through modular architecture
2Loss of information
If comprehensive usage data collection is implemented to determine usage patterns, then information completeness is improved, but loss of time increases
Solution Approach 1:
The patent implements preliminary action by having mobile devices continuously detect and log SSIDs in the background, and having infotainment systems continuously report application usage states, before any analysis is required. This pre-collection of comprehensive usage data ensures information completeness is achieved without delaying the actual usage pattern determination, as the data is already prepared and available when needed
Data Source
AI summary
An example method for classifying a service set identifier (SSID) as a vehicle SSID includes determining, by executing an instruction with a processor, that a first SSID detected by a mobile device satisfies a detection threshold, determining, by executing an instruction with the processor, that a counter of non-vehicle SSIDs different from the first SSID satisfies a quantity threshold, the counter to increment when an SSID of the non-vehicle SSIDs satisfies a time threshold, and the non-vehicle SSIDs detected while detecting the first SSID, and classifying, based on the first SSID satisfying the detection threshold and the counter of non-vehicle SSIDs satisfying the quantity threshold, the first SSID as the vehicle SSID.