Dynamic Proximity Measurement Using Travel Area Analysis
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Solution Overview
Problem
Existing geofence-based systems for location-based services use static proximity thresholds, which fail to account for user-specific environments and behaviors, leading to inaccurate notifications regarding proximity to points of interest.
Innovation Solution
A proximity measurement system that dynamically calculates a personalized geofence based on the user's typical travel area and activities, using GPS coordinates to determine an effective proximity measure as a percentage of the reference distance, which adapts to the user's context and priorities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If static proximity thresholds are used for geofence-based notifications, then the system is simple to implement, but the notification accuracy and context-awareness deteriorate
Solution Approach 1:
The patent transforms static geofence boundaries into dynamic ones by continuously adjusting the effective proximity measure based on user behavior patterns. The system calculates travel areas from historical GPS data and dynamically modifies notification thresholds according to the user's current location relative to their typical routes, making the geofence adaptive rather than fixed.
Solution Approach 2:
The system changes the proximity threshold parameter dynamically by calculating an effective proximity measure that is a percentage of the reference distance. This parameter is adjusted based on multiple factors including the user's travel area, distance to point of interest, and task priority, allowing the same physical location to trigger notifications at different distances depending on context.
2Measurement precision
If personalized dynamic geofences are implemented, then notification accuracy and context-awareness improve, but computational requirements and processing time increase
Solution Approach 1:
The system performs preliminary calculations by pre-computing the user's travel area from historical GPS data and storing it for future reference. This travel area calculation is done in advance so that when proximity notifications are needed, the system only needs to compare current location against the pre-computed area rather than performing complex spatial analysis in real-time.
Solution Approach 2:
The patent replaces complex real-time spatial analysis with simpler geometric comparisons. Instead of performing continuous path analysis or machine learning inference at notification time, the system uses pre-computed travel areas and simple distance calculations to determine effective proximity, significantly reducing processing requirements.
3Productivity
If static geofence thresholds are used, then false alerts are reduced through simple boundary definitions, but relevant notifications are missed due to lack of user context
Solution Approach 1:
The system uses user behavior data as feedback to continuously refine proximity measurements. By analyzing historical GPS trajectories and calculating travel areas, the system learns the user's typical routes and adjusts the effective proximity measure accordingly. This feedback loop ensures that notifications are triggered based on actual user context rather than arbitrary static boundaries.
Solution Approach 2:
The effective proximity measure dynamically adapts to user context by adjusting the percentage of reference distance based on the user's relationship to their travel area and the point of interest. This dynamic adjustment ensures that notifications are contextually relevant without requiring complex real-time analysis of user intent.
Data Source
AI summary
Various systems and methods for providing a proximity measurement system are provided herein. A proximity measurement system includes: a user tracking service to calculate a travel area of a user, the travel area representing an area that the user has traveled within during a period of time, a proximity service to: identify a reminder task created by the user, the reminder task having an associated point of interest; identify a plurality of geographical locations of the point of interest; and calculate an effective proximity measure based on the travel area of the user and the plurality of geographical locations; and a notification service to transmit a notification to the user when the user is within the effective proximity measure of any one of the plurality of geographical locations.