Smoothing Transformation for User Location Stability
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Solution Overview
Problem
Existing location determination methods often lack accuracy and stability, particularly in dynamic environments, leading to incorrect location assessments and inefficient navigation.
Innovation Solution
A computer-implemented method that uses a location history and device sensor data, such as acceleration and rotation, to apply a smoothing transformation and determine a predicted location, improving the stability of user device location determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional location determination methods (GPS, IP address, cell triangulation) are used, then location data can be obtained, but the accuracy and stability of the location are insufficient leading to incorrect location assessments
Solution Approach 1:
The system performs preliminary actions by collecting and storing location history data before it is needed for prediction. Location data is continuously gathered from multiple sources (GPS, Wi-Fi, cell towers) and stored in a database, preparing the foundation for future predictive calculations that will improve both accuracy and stability
Solution Approach 2:
The system implements feedback by continuously comparing predicted locations with actual sensor data and location history. The prediction module uses feedback from location deviations and sensor information to refine and adjust predicted locations, thereby improving both measurement precision and reliability over time
2Reliability
If location history and sensor data are integrated with smoothing transformation, then location stability is improved, but computational complexity increases
Solution Approach 1:
The system segments the location determination process into distinct functional modules: a collection module that gathers raw location data from multiple sources, a prediction module that applies smoothing transformations to historical data, and a determination module that integrates sensor data with predictions. This segmentation manages computational complexity by distributing processing tasks across specialized components
Solution Approach 2:
The system applies partial action by selectively using location history data within optimized time windows and applying smoothing transformations only to relevant historical data points. This approach improves location stability through predictive filtering while avoiding the computational burden of processing complete historical datasets
Data Source
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AI summary
Systems and methods for improving a stability of a displayed user location using location history are provided. In one embodiment, the method can include obtaining a location history of a user device corresponding to the user, and determining one or more predicted locations of the user device based at least in part on an application of a smoothing transformation to the location history. The method can further include determining a location of the user device based at least in part on the predicted locations of the user device, and providing the location of the user device to a display device for display.