Wireless Position Estimation Using Source-Weighted Database Records
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wireless beacon-based positioning systems suffer from systematic inaccuracies due to 'arterial bias' and require extensive data collection, making them unreliable for estimating device location with small data sets, and they fail to effectively integrate observations from different devices to improve accuracy.
Innovation Solution
A method that combines observations from different devices by considering the quality of matches and the properties of the contributing devices, allowing for intelligent integration of records from personal and shared databases to produce more accurate position estimates by weighting matches based on specificity and source reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a shared database is used to store wireless beacon observations from multiple devices, then the coverage and availability of position estimation data is improved, but systematic inaccuracies arise due to arterial bias from overrepresentation of frequently visited locations
Solution Approach 1:
The patent applies local quality by differentiating between two types of database records: personal records (from the device itself) and shared records (from other devices). The system selectively weights and combines these records based on their source and quality characteristics, giving appropriate priority to personal records while still utilizing shared records when personal records are unavailable or insufficient.
Solution Approach 2:
The system dynamically adjusts the weighting and selection of database records based on the specific situation. It evaluates quality characteristics of matches and indications of source for each record, adapting the position estimation process to favor more reliable data sources in different contexts rather than using a fixed approach.
2Quantity of substance
If extensive war-driving data collection is performed to populate the database, then the quantity of position estimation data is improved, but the time and resources required for data collection increase significantly
Solution Approach 1:
The patent merges observations from multiple devices into a shared database, allowing collective data accumulation. Instead of requiring exhaustive war-driving by a single device, the system combines data from many devices to achieve comprehensive coverage, significantly reducing the time and resources needed for data collection.
Solution Approach 2:
Each device contributes its own observations to the shared database, performing self-service data collection. Devices automatically record and submit their wireless beacon observations, eliminating the need for dedicated war-driving expeditions and enabling continuous, distributed data accumulation.
3Reliability
If only personal observations from the device itself are used for position estimation, then the relevance to the device's usual movements is improved, but the accuracy deteriorates when personal data is limited or unavailable
Solution Approach 1:
The patent creates a composite position estimation system that combines personal observations and shared observations from other devices. The final position estimate is derived from a weighted combination of personal matches and shared matches, leveraging the strengths of both data sources to achieve both relevance and accuracy.
Solution Approach 2:
The system dynamically adjusts the balance between personal and shared data based on availability and quality. When personal data is sufficient and high-quality, it receives higher weight; when personal data is limited or low-quality, the system automatically increases reliance on shared data, adapting to the situation in real-time.
4Measurement precision
If shared database records from other devices are used to supplement personal data, then the accuracy of position estimation is improved by reducing arterial bias, but the complexity of data integration and matching increases
Solution Approach 1:
The patent segments the database into distinct personal and shared components with different characteristics and quality indicators. This segmentation allows the system to apply different evaluation criteria and weighting strategies to each type of record, simplifying the integration process compared to treating all records uniformly.
Solution Approach 2:
The system employs feedback mechanisms by evaluating quality characteristics and indications of source for each match, then using this evaluation to weight and combine results. This feedback loop enables intelligent data integration that automatically adjusts to data quality, reducing the effective complexity of integration through systematic decision-making.
Data Source
AI summary
A method and apparatus for estimating the position of an electronic device. The method comprises: receiving an observation comprising the identity of at least one wireless transmitter detected by the device at the position to be estimated; comparing the observation with the contents of a set of records; detecting respective first and second matches between the observation and records, and retrieving the corresponding positions. The method comprises estimating the position of the electronic device based on at least one of the first position estimate and the second position estimate, depending upon quality characteristics of the first match and the second match and indications of the sources of the respective records.