Polygon Geofence Selection for Mobile Location Targeting
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Solution Overview
Problem
Collecting and efficiently utilizing location information from mobile device users for personalized experiences is challenging due to difficulties in processing and managing large volumes of data effectively.
Innovation Solution
A push notification platform that processes location and analytics data by indexing devices based on their location and time, allowing for efficient querying and targeting of specific user groups for personalized notifications, while also providing tools for composing and validating push notifications across different operating systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If location information is collected from mobile device users, then personalized experiences can be provided, but efficient processing and management of large volumes of data becomes difficult
Solution Approach 1:
The patent segments location data into discrete geofences with unique identifiers, dividing the continuous location space into manageable discrete units. This segmentation allows the system to handle large volumes of location data efficiently by processing only relevant geofence transitions rather than continuous coordinate streams.
Solution Approach 2:
The patent introduces a temporal dimension by recording timestamp information alongside geofence transitions, and a hierarchical dimension through nested geofence structures. This multi-dimensional approach enables efficient querying and analysis of location patterns without processing all raw location data.
2Speed
If location data is processed in real-time, then timely push notifications can be sent, but processing speed and system performance may be compromised
Solution Approach 1:
The system pre-defines geofences and their boundaries before runtime, so that when location data arrives, the system only needs to check against pre-computed geometric shapes rather than performing complex spatial analysis in real-time. This preliminary preparation enables fast query processing.
Solution Approach 2:
The patent creates simplified representations of geographic locations using geometric shapes (polygons, circles, rectangles) that approximate real-world boundaries. These simplified geometric copies enable fast computational operations while maintaining sufficient accuracy for push notification purposes.
3Measurement precision
If precise geolocation targeting is implemented, then user engagement improves, but data management complexity increases
Solution Approach 1:
The patent implements nested geofences where smaller geofences can be contained within larger ones, creating a hierarchical structure. This nesting allows the system to manage precise location targeting at multiple scales simultaneously, from broad regional areas to specific building-level locations, without linearly increasing complexity.
Solution Approach 2:
The system allows dynamic adjustment of geofence parameters such as boundary coordinates, radius, and inclusion/exclusion status. By parameterizing geofence definitions, the system can precisely control targeting accuracy while managing complexity through configurable parameters rather than hard-coded logic.
Data Source
AI summary
Selecting a geolocation using a polygon is disclosed. User input is received. One or more polygons used to define an audience are determined based at least in part on the received user input. At least one polygon is displayed. Content is sent to the audience defined by the polygon in response to a received confirmation of the at least one polygon.