Contextual Location Anchor Detection for Personalized Geospatial Services
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Solution Overview
Problem
Current methods for determining and utilizing location-based information relevant to a user's daily life are inefficient, relying on pre-existing databases and geo-coordinate mappings, which fail to provide contextually relevant geographical locations automatically.
Innovation Solution
A system that determines location-based data associated with a user, identifies stationary points, and calculates context data to establish location anchors representing bounded geographical areas of contextual relevance, allowing for automatic recognition and presentation of personally relevant locations without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If geometry-based or fingerprint-based methods are used to determine places of interest, then location information can be retrieved from pre-existing databases, but the methods fail to provide contextually relevant geographical locations automatically
Solution Approach 1:
The system automatically analyzes user location data, device information, and context data to self-determine relevant geographical locations without requiring manual user input or intervention. The processor autonomously identifies location anchors based on the collected data patterns.
Solution Approach 2:
The system collects and processes location-based data, device data, and context data in advance to pre-determine location anchors before they are needed for service delivery, enabling faster and more relevant information retrieval when users need location-based services.
2Adaptability or versatility
If pre-existing databases and geo-coordinate mappings are used, then location data can be stored and retrieved, but the system cannot effectively determine geographical locations relevant to a particular user's daily life
Solution Approach 1:
The system customizes location information specifically for each user by analyzing their individual location patterns, device characteristics, and contextual data, providing personalized location anchors rather than generic geographical information.
Solution Approach 2:
The system divides the complex task of determining relevant locations into distinct processing stages: collecting location-based data, acquiring device data, gathering context data, and synthesizing this information to identify location anchors, making the overall process more manageable and effective.
3Ease of operation
If manual user intervention is required to provide location information, then accuracy can be maintained, but user convenience and efficiency are reduced
Solution Approach 1:
The system automatically collects and processes location data, device information, and context data without requiring manual user input, while maintaining high accuracy through multi-source data validation and pattern recognition algorithms.
Data Source
AI summary
An approach is provided for determining and utilizing geographical locations contextually relevant to a user. A contextually relevant location platform determines location-based data associated with a user and/or user device. The contextually relevant location platform determines stationary points based, at least in part, on the location-based data. The contextually relevant location platform determines context data associated with the stationary points. The contextually relevant location platform determines at least one location anchor based, at least in part, on the stationary points and the associated context data, wherein the at least one location anchor represents a bounded geographical area of contextual relevance to the user.