Mobile Location Correction via Device Density Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The accuracy of mobile location data is inconsistent due to varying device capabilities and the lack of secondary location data, leading to inaccurate device location estimation and subsequent errors in location-based services.
Innovation Solution
A computer-implemented method and system that corrects location data by using a device density map to determine a set of possible geographic locations and calculate probabilities for each location, selecting the most likely true location based on historical device distribution, and publishing this corrected location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If mobile service providers use cell tower location data, then location data can be obtained without native applications, but the location accuracy deteriorates to hundreds of meters due to cell site location limitations
Solution Approach 1:
The patent introduces a location correction system as an intermediary between the mobile service provider and the location-based service platform. This system receives location data from cell tower measurements, processes it through probability calculations based on device density maps, and outputs corrected location estimates. The intermediary transforms inaccurate cell tower location data into more accurate location information without requiring changes to the mobile service provider's data collection methods.
Solution Approach 2:
The patent replaces the direct use of cell tower location data with a probabilistic computational model. Instead of relying on the physical limitation of cell tower coverage areas, the system uses device density maps and probability calculations to estimate the true location. This substitution transforms a mechanical measurement problem into an information processing problem that can be solved through data analysis.
2Measurement precision
If GPS or WiFi triangulation is used to improve location accuracy, then location precision improves to within meters, but device complexity and user configuration requirements increase
Solution Approach 1:
The location correction system operates autonomously without requiring user intervention. It automatically receives location data from mobile devices, processes the data through its probabilistic model, and outputs corrected locations. The system self-corrects location inaccuracies without users needing to configure GPS, WiFi triangulation, or any other location services, making the complexity invisible to the end user.
Solution Approach 2:
The system performs preliminary correction of location data before it is used by location-based services. By pre-processing the location data through device density maps and probability calculations, the system ensures accurate location information is available downstream without requiring other systems to perform complex location processing or user configuration.
3Productivity
If mobile service providers truncate or round location coordinates, then data transmission is simplified, but location precision deteriorates due to rounding errors
Solution Approach 1:
The location correction system acts as an intermediary that receives truncated location data from mobile service providers, processes it through probabilistic modeling, and outputs high-precision corrected locations. This intermediary approach allows the system to work with simplified input data while producing precise output, decoupling the data transmission simplicity from the final location precision requirement.
Data Source
AI summary
A location correction system receives a reported location of a mobile device. A set of possible geographic locations for the mobile device is determined based at least in part on the reported location and a device density map describing a historical distribution of mobile devices over a geographic region. A probability is determined for each location in the set of possible geographic locations, each probability indicating a likelihood that an associated possible geographic location represents a true location of the mobile device. Responsive to the determined probabilities, a possible geographic location in the set is selected. A true location of the mobile device is published based at least in part on the selected possible geographic location.