Dynamic Geo-Fences for Context-Aware Merchant Discovery
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Solution Overview
Problem
Users face inefficiencies in finding nearby merchants that meet their needs due to the time-consuming nature of searching through large lists provided by online websites and mobile applications, which do not effectively utilize user history, transportation mode, or real-time conditions to identify relevant merchants.
Innovation Solution
A system dynamically reconfigures geo-fences based on user history, transportation mode, navigation routes, and real-time conditions to identify and display nearby merchants that are likely to be of interest, reducing the need for manual specification by the user and conserving battery life and processing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed radius geo-fence is used to identify nearby merchants, then the search area is clearly defined, but users must manually sift through all merchants in that area regardless of relevance
Solution Approach 1:
The patent transforms the static fixed-radius geo-fence into a dynamic search boundary that automatically adjusts its shape and extent based on real-time user context including transportation mode, navigation routes, and historical behavior patterns. This dynamic adjustment allows the system to expand or contract the search area intelligently, presenting only relevant merchants to users without requiring manual filtering of irrelevant results.
Solution Approach 2:
The system changes the parameters defining the search area from a simple fixed radius to a complex multi-dimensional boundary informed by user history data, current transportation mode, and navigation context. This parameter transformation enables the geo-fence to adapt its characteristics (size, shape, position) based on varying user needs and environmental conditions.
2Measurement precision
If multiple data sources are integrated to dynamically adjust geo-fences, then merchant identification accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the complex task of merchant identification into distinct functional modules: a data collection module that gathers user history and context information, a geo-fence configuration module that processes this data and defines search boundaries, and a merchant identification module that queries for relevant merchants. This segmentation manages system complexity by organizing functions into independent, manageable components.
Solution Approach 2:
The system introduces a geo-fence configuration service as an intermediary layer between raw user data and merchant search results. This intermediary processes multiple data sources (user history, transportation mode, navigation routes) and transforms them into a structured geo-fence definition that guides the merchant search, simplifying the overall system architecture.
3Productivity
If continuous location monitoring and data processing are performed, then real-time merchant recommendations are provided, but battery consumption increases
Solution Approach 1:
The system implements periodic action by updating the geo-fence configuration at specific trigger events rather than continuously. The geo-fence is recalculated when significant changes occur, such as when the user's transportation mode changes, when a new navigation route is established, or when the user enters a new geographic area. This event-driven approach maintains real-time responsiveness while minimizing unnecessary processing and energy consumption.
Data Source
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AI summary
Geo-fences may be dynamically reconfigured to identify merchants that may be of particular interest to users. In some instances, a geo-fence may be defined for a particular user based on a variety of information, in order to identify merchants that may be of interest to the user and that are located within proximity to the user. The geo-fence may be defined based on purchase history, places that are frequented by the user, a mode of transportation, a navigation or transportation route, user preferences, and/or a variety of other information. Information regarding the identified merchants may be displayed or otherwise output to notify the user of nearby merchants that may be of interest.