Hierarchical Grid Cell Identifier System for Mobile Location Tracking
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Solution Overview
Problem
Current location determination systems, such as those using GPS, are inefficient in determining whether a mobile device is within a specific geographical region, as they rely on computational intensive methods like Ray Casting and do not provide sufficient information about the device's location context, such as being within a store, home, or commercial district.
Innovation Solution
A computationally efficient method and system using a hierarchical grid system to determine if a mobile device is within a predetermined geographical boundary by converting location coordinates into cell identifiers, allowing for efficient searching within a set of cell identifiers representing the region, thereby improving precision and reducing computational intensity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Ray Casting method is used to determine whether a mobile device is within a geographical region, then measurement precision is improved, but computational complexity increases
Solution Approach 1:
The geographical region is divided into a hierarchical grid system with multiple levels of resolution. Each grid cell is represented by simple coordinate boundaries instead of complex polygonal shapes. This segmentation transforms the continuous geographical space into discrete, manageable units that can be efficiently queried without requiring computationally intensive ray casting operations.
Solution Approach 2:
The patent uses simplified grid cell representations instead of precise polygonal region definitions. Each grid cell is defined by simple minimum and maximum coordinates, which are computationally cheap to store and query. This approximation trades some geometric precision for significant reductions in computational complexity, allowing rapid location queries.
2Loss of information
If GPS coordinates are used to represent location, then position information is obtained, but sufficient context information about location is not provided
Solution Approach 1:
The patent introduces grid cell identifiers as an intermediary representation between raw GPS coordinates and high-level location context. Instead of directly interpreting coordinates to determine location context, the system maps coordinates to grid cells, which then serve as keys to retrieve pre-computed region information. This intermediary layer efficiently bridges the gap between precise coordinates and meaningful location context.
Solution Approach 2:
The system pre-computes and stores the relationships between grid cells and geographical regions before runtime queries. Region boundaries are preprocessed to determine which grid cells intersect with which regions, and this information is stored for rapid retrieval. This preliminary action eliminates the need for complex real-time geometric computations during location queries.
3Measurement precision
If high precision location tracking is implemented, then measurement precision is improved, but user privacy is compromised
Solution Approach 1:
The patent segments continuous location data into discrete grid cell identifiers. Instead of storing or processing precise continuous coordinates, the system uses integer-based grid cell IDs that represent approximate locations. This segmentation maintains sufficient precision for region determination while inherently obscuring exact position information, thereby protecting user privacy.
Solution Approach 2:
The system uses simplified integer coordinates for grid cells instead of precise floating-point GPS coordinates. These integer representations are computationally cheap and provide sufficient resolution for determining whether a device is within a region, while deliberately sacrificing the precision needed to identify exact locations, thus protecting user privacy.
Data Source
AI summary
Systems and methods including computing patterns of visitation to predefined regions by converting coordinates of mobile devices to cell identifiers and searching a database to find matches between cell identifiers representing regions and the cell identifiers of the device locations. Devices having similar visitation patterns are divided into two groups, based on status data of whether or not information about a region has been transmitted to respective users. The visitation patterns after the transmission are compared by a system between the two groups to measure a difference. Identifiers of devices, users, or households are initially provided to the system without the status data to obtain attributes associated individually with the identifiers. In return, the system is provided with the status data associated with the attributes individually for the devices, users, or households but without sufficient information to map the status data individually to the identifiers of the devices, users, or households.