Location Derivation Using Movement Pattern Deviation
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Solution Overview
Problem
The increasing portability of electronic devices has led to a decrease in battery capacity, as they consume significant power for location services, particularly due to frequent GPS and satellite transmissions, resulting in reduced battery life and the need for more frequent recharging.
Innovation Solution
A method and device that utilize a first low-power sensor to measure movement and derive a typical movement area and schedule, initiating a second sensor only when the device deviates from this pattern, thereby conserving battery life by reducing the need for frequent high-power location determinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS and satellite transmissions are used frequently for location services, then location accuracy is improved, but battery consumption increases
Solution Approach 1:
The system uses periodic action by implementing a learning phase followed by a maintenance phase. During the learning phase, GPS is used frequently to establish baseline location data. During the maintenance phase, the system periodically compares current location estimates (from lower-power sensors) against the learned baseline, only activating high-power GPS when significant deviations are detected, thus reducing overall battery consumption while maintaining location accuracy.
Solution Approach 2:
The system dynamically adjusts its location determination strategy based on learned patterns. It transitions from a static approach of continuous or periodic GPS usage to a dynamic approach where GPS is activated only when necessary (when location deviation exceeds thresholds). This dynamic adaptation allows the system to optimize between location accuracy and battery consumption based on actual usage patterns.
2Volume of moving object
If electronic devices are made more portable with smaller batteries, then device portability is improved, but battery life decreases
Solution Approach 1:
The system changes operational parameters by switching between different location determination methods based on power consumption characteristics. It uses learned location patterns to determine when high-power GPS is necessary versus when lower-power alternatives suffice, effectively changing the power consumption parameter dynamically to extend battery life in portable devices.
Solution Approach 2:
The system provides self-service by automatically learning and adapting to user location patterns without manual intervention. The learning phase automatically establishes baseline data, and the maintenance phase automatically compares current positions against this baseline, enabling the device to self-optimize its power consumption for location services.
3Productivity
If continuous location monitoring is performed, then location availability is improved, but power consumption increases
Solution Approach 1:
The system applies partial action by using lower-power location estimation methods for routine monitoring and reserving high-power GPS only for exceptional cases where location deviation is detected. This partial use of high-power resources maintains location availability while significantly reducing overall power consumption compared to continuous GPS monitoring.
Solution Approach 2:
The system introduces an intermediary comparison mechanism that acts as a mediator between continuous location monitoring and high-power GPS usage. The learned baseline location data serves as an intermediary reference point, allowing the system to detect when actual location deviates significantly, thereby triggering GPS only when necessary rather than using it continuously.
Data Source
AI summary
A method and device for deriving a location. The method includes measuring, with a first sensor, movement as a function of time during a first period of time; deriving a typical movement area and a typical movement schedule using the measured movement; measuring, with the first sensor, movement as a function of time during a second period of time, wherein the second period of time corresponds to the first period of time; comparing the measured movement as a function of time during the second period of time with the derived typical movement area and the typical movement schedule; and initiating a second sensor to determine a current location if the measured movement as a function of time during the second period of time is not within the derived typical movement area or not aligned with the derived typical movement schedule based on the comparison.