Geo-fence Valuation System Using Precision-Based Geodensity Augmentation
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Solution Overview
Problem
Accurately determining the number of devices within a geo-fenced area is challenging due to varying location data precision from methods like cell towers, Wi-Fi, and GPS, which can overlap multiple areas, making it difficult to generate an accurate count.
Innovation Solution
A geo-fence valuation system that collects usage data from client devices, identifies data types based on precision levels, and calculates geodensity by counting unique devices within the area, augmenting the count based on data types to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple location data methods (cell towers, Wi-Fi, GPS) are used to determine device location, then the coverage area is improved, but the measurement precision deteriorates due to overlapping areas and varying precision levels
Solution Approach 1:
The patent segments the usage data by data type (GPS, cellular, Wi-Fi) and processes each segment separately to determine device presence. By dividing the location data into distinct categories with different precision characteristics, the system can apply appropriate weighting and validation rules to each segment, thereby maintaining measurement precision while preserving comprehensive coverage from multiple data sources.
2Quantity of substance
If location data with lower precision is included to increase device detection coverage, then the quantity of detected devices is improved, but the reliability of the device count deteriorates
Solution Approach 1:
The patent applies local quality by treating different data types with different levels of trust based on their inherent precision characteristics. GPS data receives higher weight and stricter validation thresholds, while cellular and Wi-Fi data receive lower weight and more lenient thresholds. This localized quality assignment allows the system to maximize device detection while maintaining reliability by not treating all location data equally.
Solution Approach 2:
The system changes parameters by adjusting the confidence thresholds and weighting factors based on data type. For lower precision data types, the system modifies the parameters used in device presence determination, such as allowing greater temporal flexibility or requiring corroboration from multiple sources, thereby balancing quantity of detected devices with reliability of the count.
3Measurement precision
If all available location data types are processed to improve geodensity accuracy, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-categorizing and pre-processing location data into distinct data types before analysis. Usage data is segmented by data type (GPS, cellular, Wi-Fi) and pre-tagged with metadata indicating precision level and reliability characteristics. This preliminary organization reduces the complexity of subsequent processing by eliminating the need for real-time data type identification and enabling parallel processing of different data segments.
Data Source
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AI summary
Disclosed, is a geo-fence valuation system to: access usage data at a server system, the usage data collected from a set of client devices located within a geo-fenced area, and wherein the usage data comprises data objects, wherein each data object includes at least a device identifier of a source device of the usage data, and location data; identify one or more data types of the location data, wherein the data types indicate a level of precision of the location data; determine a geodensity of the geo-fenced area based on the usage data, wherein the geodensity indicates at least a number of client devices located within the geo-fenced area; and augments the geodensity of the geo-fence based on the one or more data types of the location data.