Location Data Clustering for Visit Accuracy
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Solution Overview
Problem
Mobile devices record numerous location points with varying geographic coordinates, leading to inaccuracies in tracking user visits, as consecutive points may not be recognized as a single location due to differences in coordinates, resulting in incomplete location history.
Innovation Solution
The method constructs 'time blocks' by identifying chronologically consecutive location points with predefined speed and accuracy thresholds, scoring adjacent points to determine if they represent the same location, and combining them to represent a single visit, with a system that includes a server to analyze and consolidate these blocks for determining frequently visited locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If location data is recorded with high precision coordinates, then measurement precision is improved, but the same location appears as multiple different locations due to coordinate variations
Solution Approach 1:
The patent merges multiple location points that fall within a threshold distance of each other into a single consolidated location entry. This combines redundant data representing the same physical location while filtering out minor coordinate variations, thereby resolving the contradiction between maintaining precise coordinates and ensuring reliable location history.
2Reliability
If user assistance is required to correct location issues, then location history accuracy is improved, but device complexity and operational ease deteriorate
Solution Approach 1:
The system automatically processes and corrects location data without requiring user intervention. It self-corrects coordinate inaccuracies, consolidates duplicate location entries, and generates accurate location history autonomously, eliminating the need for manual user assistance while maintaining high reliability.
3Quantity of substance
If thousands of location points are recorded, then data completeness is improved, but data processing complexity and time consumption increase
Solution Approach 1:
The patent extracts and removes redundant location data by identifying and consolidating duplicate entries within threshold distances. This extraction process eliminates unnecessary data points while preserving essential location information, thereby reducing processing complexity and improving efficiency without sacrificing data completeness.
Data Source
AI summary
Systems and methods are disclosed for determining locations visited by a mobile device. In an embodiment, a first location point is identified from a plurality of location points associated with the mobile device. The first location point may be combined with one or more of the plurality of location points to construct a time block. A time block may indicate a continuous period of time when the mobile device is in the same location. An aggregate location is calculated for the time block based on the plurality of points in the time block. One or more time blocks may be grouped based on the aggregate location of each time block, and a spatial clustering procedure is applied to transform the aggregate locations of time blocks in the group into one or more locations of interest.