Aggregating Mobile Battery Data via Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Mobile devices face challenges in extending battery life due to varying power consumption by hardware and software components, with existing methods lacking comprehensive data aggregation and correlation to improve battery efficiency.
Innovation Solution
A system and method for collecting, correlating, and aggregating battery life data from multiple mobile devices based on characteristics such as software builds and usage patterns, enabling the generation of reports that identify usage patterns impacting battery life and facilitating improvements in battery performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If battery life data is collected and aggregated from multiple mobile devices with different characteristics, then the ability to detect usage patterns and software regressions improves, but the complexity of data management and analysis increases
Solution Approach 1:
The patent segments battery life data by grouping mobile devices according to their characteristics (software builds, hardware configurations, usage patterns). This segmentation allows for comparable analysis within homogeneous groups while managing the overall data complexity through structured categorization.
Solution Approach 2:
The patent changes the parameters used for data aggregation by correlating battery life data with multiple device characteristics simultaneously. This multi-parameter approach enables more precise detection of usage patterns and software regressions while organizing complex data through defined correlation parameters.
2Reliability
If comprehensive battery life data is aggregated across different software builds, then the ability to identify software release regressions improves, but the difficulty of correlating and analyzing the data increases
Solution Approach 1:
The patent creates a universal data aggregation framework that handles multiple software builds and device characteristics through a common correlation methodology. This universal approach enables consistent detection of software regressions across different versions while simplifying the correlation process through standardized procedures.
Solution Approach 2:
The patent implements feedback mechanisms where aggregated battery life data from multiple software builds is analyzed to identify regressions, which then inform future software development and testing. This feedback loop improves regression detection reliability while managing correlation complexity through iterative refinement.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Battery life data may be collected from a number of mobile devices. The battery life data for each of the mobile devices may be correlated with one or more characteristics of each of the mobile devices. The battery life data for the mobile devices may be aggregated based on at least one of the one or more characteristics. In some examples, a report of the aggregated battery life data for the mobile devices including at least one common characteristic is generated.