Inferring Beacon Positions via Spatial Graph Relationships
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Solution Overview
Problem
Existing positioning systems face challenges in accurately determining the location of beacons lacking beacon reference data, as the accuracy of estimated device locations depends on the quantity of beacons with known positions, and existing methods struggle to increase the number of known beacons without GPS information.
Innovation Solution
A collaborative positioning system estimates the location of beacons based on spatial relationships with neighboring beacons by accessing beacon reference data and performing set operations, such as graph modeling and calculations using SQL, to infer positions of beacons without reference data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If beacon positions are calculated based on signal strength and broadcast characteristics, then the quantity of beacons with known position increases, but the accuracy of position estimation deteriorates
Solution Approach 1:
The patent introduces an intermediary computational process that uses spatial relationships and graph theory to mediate between observed beacon lists and position estimation. By modeling beacons as nodes in a graph and using set operations to infer positions from spatial relationships, the system can estimate positions of beacons without direct GPS measurements, thereby increasing the quantity of known beacons while maintaining reasonable accuracy through mathematical relationships rather than direct signal strength measurements
Solution Approach 2:
The patent replaces the mechanical/physical approach of using signal strength and broadcast characteristics for position calculation with a computational/mathematical approach. By substituting the physical signal-based method with graph theory and set operations, the system achieves position estimation that scales better and can handle larger quantities of beacons while maintaining consistency through mathematical rather than physical measurement relationships
2Reliability
If more beacons are included in positioning calculations, then the location query success rate improves, but the complexity of processing beacon data increases
Solution Approach 1:
The patent segments the beacon data processing into distinct computational stages: building the graph structure from observed beacon lists, performing set operations to identify spatial relationships, and calculating positions based on inferred relationships. This segmentation allows the system to handle large quantities of beacons systematically, improving location query success rate while managing processing complexity through structured, modular computation rather than monolithic processing
Data Source
AI summary
Estimating positions of beacons based on spatial relationships among neighboring beacons. Beacon reference data defining positions of beacons is stored from beacon fingerprints observed by devices (e.g., enabled with global positioning system receivers). For a received beacon fingerprint having at least one beacon for which the beacon reference data is missing (e.g., from a device without a GPS receiver), beacons in the received beacon fingerprint for which beacon reference data is available are identified. Based on these identified beacons, the missing beacon reference data is calculated. In some embodiments, a set of spatially diverse beacons is selected from the identified beacons prior to calculating the beacon reference data.