Mobile Location Identifier Generation Automation
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Solution Overview
Problem
Existing methods for generating and using location identifiers in mobile devices are complex, error-prone, and resource-intensive, and do not fully integrate with the device, placing undue demand on users and lacking integration within the device.
Innovation Solution
A mobile device with a positioning module to obtain location history and a processing module to determine significant locations, automatically generate potential location identifiers, and prompt users for input to refine these identifiers at appropriate times, integrating user input for customized location identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automated location identifier generation is implemented using existing methods, then location information can be extracted from location history, but the process becomes complex, error-prone and resource intensive
Solution Approach 1:
The patent segments the location identifier generation process into distinct modules: a location history module that collects raw location data, a processing module that analyzes the data to identify significant locations, and a generation module that creates location identifiers. This segmentation isolates complexity into manageable components, reducing overall system complexity while maintaining automation.
Solution Approach 2:
The patent performs preliminary actions by pre-processing location history data to identify significant locations and patterns before generating location identifiers. The system pre-analyzes location data to determine dwell times, visit frequencies, and spatial patterns, preparing structured information that simplifies the subsequent identifier generation process and reduces computational complexity.
2Productivity
If existing automated methods are used for location identifier generation, then location information can be extracted, but errors increase and resource consumption increases
Solution Approach 1:
The patent implements feedback mechanisms where the processing module continuously refines location identifier generation based on analyzed location history patterns. The system uses feedback from dwell time calculations, visit frequency analysis, and spatial pattern recognition to adjust and improve the accuracy of generated location identifiers, reducing errors while maintaining high productivity.
Solution Approach 2:
The system performs self-service by automatically validating and refining location identifiers through internal consistency checks against the location history data. The processing module self-corrects potential errors by cross-referencing generated identifiers with actual location patterns, reducing reliance on external validation resources while improving reliability.
3Measurement precision
If manual user input is required for location identifier refinement, then accuracy can be improved, but user burden increases
Solution Approach 1:
The patent applies partial action by requiring user input only for specific critical decisions in the location identifier refinement process, rather than demanding complete manual validation. The system automatically handles routine identifier generation and only prompts users when alternative interpretations exist or when high-confidence identifiers need confirmation, reducing user burden while maintaining precision.
Solution Approach 2:
The processing module acts as an intermediary between raw location data and user interaction. It translates complex location history analysis into simplified presentation options for users, mediating between automated generation and manual refinement. This intermediary layer filters out routine decisions requiring no user input while presenting only meaningful choices that improve precision.
Data Source
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AI summary
A method and apparatus for generating and using location information is provided to a user of a mobile device. The method involves obtaining (110) and processing a location history of the mobile device to determine locations of significance (120); automatically generating potential location identifiers (130) associated with the locations of significance; and prompting (150), at a determined appropriate time (140), for user input for refining the set of one or more potential location identifiers into a customized location identifier.