Indoor Positioning Quality Metrics for Radio Mapping Gaps
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Solution Overview
Problem
Existing indoor positioning systems face challenges in achieving accurate positioning and floor detection indoors due to the lack of scalable, cost-effective solutions that utilize existing infrastructure and device capabilities, and there is a need for evaluating the sufficiency of data collection and radio infrastructure to ensure high-quality positioning.
Innovation Solution
A method and apparatus that determine a third metric based on collected radio data to evaluate the quality of infrastructure and suggest corrective actions, such as adding radio nodes, to ensure sufficient data collection and infrastructure for accurate indoor positioning and floor detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual exhaustive radio surveying is performed to achieve high positioning accuracy, then positioning quality improves, but deployment time and cost increase significantly
Solution Approach 1:
The system performs radio mapping only in areas where it is actually needed rather than conducting exhaustive surveys of entire buildings. The quality assessment metrics identify regions with sufficient radio infrastructure and data, allowing selective focus on areas requiring additional surveying efforts.
Solution Approach 2:
The system continuously assesses radio mapping quality using multiple metrics (coverage percentage, sample density, positioning accuracy) and provides feedback to guide further data collection efforts. This feedback mechanism allows dynamic adjustment of surveying priorities based on actual performance needs.
2Reliability
If manual exhaustive radio surveying is performed to ensure complete coverage, then coverage completeness improves, but deployment cost increases
Solution Approach 1:
The system achieves sufficient coverage by focusing surveying efforts on areas with inadequate radio infrastructure or data quality, rather than uniformly surveying all areas. Quality assessment identifies regions meeting coverage thresholds, eliminating unnecessary surveying costs in already-sufficient areas.
Solution Approach 2:
The system automatically assesses its own radio mapping quality and identifies areas needing improvement without requiring manual inspection or expert intervention. This self-assessment capability reduces deployment costs by eliminating labor-intensive quality verification processes.
3Measurement precision
If support for multiple positioning technologies is implemented to improve positioning accuracy, then positioning quality improves, but device complexity increases
Solution Approach 1:
The quality assessment framework is technology-agnostic and can evaluate multiple positioning technologies (Wi-Fi, Bluetooth, cellular) using the same metrics and procedures. This universal approach simplifies system design by providing a unified assessment methodology rather than requiring separate complex evaluation systems for each technology.
Solution Approach 2:
The system extracts and evaluates only the essential quality attributes (coverage, density, accuracy) that are common to all positioning technologies, separating these core metrics from technology-specific implementation details. This extraction simplifies cross-technology comparison and integration.
4Ease of operation
If radio mapping quality is not assessed, then deployment process is simpler, but positioning reliability deteriorates
Solution Approach 1:
The system provides automated feedback on radio mapping quality through computed metrics and visualizations, enabling deployers to make informed decisions about when sufficient data has been collected. This feedback loop maintains positioning reliability by ensuring quality thresholds are met while keeping the process straightforward through automated assessment.
Solution Approach 2:
The system performs self-assessment of radio mapping quality without requiring external validation or complex manual checking procedures. This self-service capability maintains positioning reliability through automated quality verification while preserving deployment simplicity by eliminating cumbersome quality assurance steps.
Data Source
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AI summary
A method is disclosed comprising: obtaining a plurality of fingerprints, wherein each fingerprint comprises a piece of position information, and wherein each fingerprint is gathered in a venue (201); determining a first metric based at least partially on the obtained plurality of fingerprints, wherein the first metric is indicative of a quality value of the obtained plurality of fingerprints (202); determining a second metric based at least partially on the obtained plurality of fingerprints, wherein the second metric is indicative of a quality value of an infrastructure of the venue (203); determining a third metric indicative of an evaluation of the quality of the infrastructure of the venue based at least partially on the the second metric (204); and outputting the first metric, the second metric and/or the third metric (205). It is further disclosed an according apparatus, computer program and system.