Dynamic Geofence Sizing for Mobile Location Detection
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Solution Overview
Problem
Existing geofencing technologies face challenges in accurately determining a mobile device's location in sparse areas due to geolocation resolution limitations, leading to potential missed notifications when the device is near a merchant location.
Innovation Solution
A mobile device generates geofences using a combination of WiFi hotspot identifications and GPS/cellular triangulation, adjusting geofence sizes based on location density to improve detection accuracy and notification reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a mobile device uses standard geolocation methods (GPS/cellular triangulation) to determine location, then the device can operate globally, but location detection accuracy deteriorates in sparse areas with limited reference points
Solution Approach 1:
The system implements different geofence generation strategies based on location density characteristics. In sparse areas, it generates larger geofences with relaxed boundary precision, while in dense areas it generates smaller, more precise geofences. This local adaptation resolves the contradiction by optimizing geofence parameters according to the specific environmental conditions rather than using a uniform approach globally.
Solution Approach 2:
The system dynamically adjusts geofence size and detection parameters based on real-time assessment of location density. When the device detects it is in a sparse area (few WiFi hotspots, poor GPS signal), it automatically enlarges the geofence radius to compensate for reduced location precision. This dynamic adjustment allows the system to maintain effective geofencing performance across varying environmental conditions.
2Reliability
If the device uses a single geofence approach, then the system is simple to implement, but detection reliability deteriorates when the device is near but outside the geofence boundary
Solution Approach 1:
The system segments the geofence detection approach into multiple components: local geofences for individual merchant locations and a triggering geofence for broader area detection. When the device exits a local geofence, it triggers a larger geofence to ensure continued monitoring. This segmentation resolves the contradiction by creating a layered detection system that maintains high reliability without requiring complete redesign of the geofence architecture.
Solution Approach 2:
The system performs preliminary assessment of location density and pre-generates appropriately sized geofences before the device enters them. By anticipating the device's movement patterns and pre-establishing geofence boundaries based on assessed location characteristics, the system ensures reliable detection while avoiding the complexity of real-time geofence recalculation during device movement.
3Measurement precision
If geofences are generated with fixed size, then the generation process is simple, but detection accuracy worsens in sparse areas where location resolution is limited
Solution Approach 1:
The system changes the size parameter of geofences based on assessed location density rather than using a fixed radius. In sparse areas, it generates larger geofences with increased radius to compensate for poorer location resolution. In dense areas, it uses smaller, more precise geofences. This parameter adaptation resolves the contradiction by allowing flexible geofence sizing that maintains detection accuracy across different environmental conditions while using straightforward radius adjustment logic.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating geofences. One of the methods includes receiving, at a mobile device, a signal emitted by a merchant device associated with a merchant. If the signal is emitted by a merchant device associated with a merchant and the distance between the mobile device and the merchant device satisfies a threshold, a notification is provided on the mobile device indicating proximity of the merchant associated with the merchant device.