Mobile Device Usage Measurement via Debug Log Filtering
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Solution Overview
Problem
Existing methods for monitoring mobile device usage are hindered by strict software installation controls, high implementation costs due to diverse device models, and lack of public APIs for interacting with mobile devices, making it difficult to gather user behavior data across various devices.
Innovation Solution
A mobile device application filters debug log files to determine usage patterns, sending filtered data to a central server for aggregation and analysis, which processes usage information to provide insights on device types, audience characteristics, and content exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing methods for monitoring mobile device usage are implemented, then usage data can be collected, but strict software installation controls and lack of public APIs make it difficult to gather user behavior data across various devices
Solution Approach 1:
The mobile device itself generates and stores debug log files that contain usage information. The system leverages the device's own logging infrastructure rather than requiring external monitoring software, allowing the device to serve itself for data collection purposes.
Solution Approach 2:
A server acts as an intermediary that receives debug log files from multiple mobile devices, aggregates the usage information, and processes the data. This intermediary handles the complexity of cross-device compatibility, allowing individual devices to remain simple while achieving versatile data collection across diverse device types.
2Quantity of substance
If existing monitoring methods are implemented across diverse device models, then comprehensive usage data can be obtained, but implementation costs become prohibitively expensive due to device-specific adaptations
Solution Approach 1:
The server infrastructure is designed to universally handle debug log files from multiple different mobile device types without requiring device-specific processing logic. A single server implementation can aggregate data from diverse devices, eliminating the need for expensive device-specific adaptations and reducing implementation costs while maintaining comprehensive data collection.
3Loss of information
If debug log files are collected from mobile devices, then detailed usage information can be gathered, but processing and analyzing the aggregated data requires significant computational resources
Solution Approach 1:
The server extracts only the relevant usage information from the debug log files during aggregation, rather than processing and analyzing entire log files. This selective extraction of needed data reduces computational energy consumption while preserving all necessary usage information for analysis.
Data Source
AI summary
Systems, methods, apparatus, and articles of manufacture to measure mobile device usage are disclosed. An example method to determine mobile device usage includes filtering, with a processor, a debug log file stored in the device to obtain debug file entries representative of device usage information, the debug log file having been modified by at least one of an operating system of the device or a device application, and sending, to a server, a filtered log file based on filtering the debug log file.