Crowd-Sourced Trusted-GPS Map for Indoor Localization
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Solution Overview
Problem
Indoor navigation in mobile devices faces challenges with inaccurate satellite-based navigation indoors, leading to delays and resource inefficiency due to high processing demands from wireless signal data, especially in lower-quality infrastructure and older devices.
Innovation Solution
A trusted-GPS system is deployed using fingerprint data and GPS position data from mobile devices, processed on a server to create a positioning map, identifying reliable GPS areas for accurate indoor positioning without additional data fusion, and utilizing these areas as geofences for commercial promotions, minimizing device resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If satellite-based navigation systems are used for indoor positioning, then positioning accuracy may be improved in areas with signal availability, but the system becomes unavailable or sporadically available in enclosed or partly enclosed urban infrastructure and buildings
Solution Approach 1:
The patent segments the indoor area into multiple zones with different GPS reliability characteristics. By dividing the environment into distinct regions (trusted-GPS zones vs. non-trusted zones), the system can selectively apply different positioning strategies in different areas, maintaining accuracy where possible while ensuring reliability where GPS is unavailable.
Solution Approach 2:
The system performs preliminary crowd-sourced GPS testing and fingerprint data collection before actual navigation. By pre-mapping GPS availability and creating positioning maps in advance, the system establishes trusted-GPS regions beforehand, allowing it to switch between positioning methods seamlessly during actual use without real-time processing delays.
2Reliability
If wireless signal data processing is performed to improve indoor positioning accuracy, then positioning reliability is improved, but processing demands increase causing delays and resource inefficiency
Solution Approach 1:
The system performs wireless signal fingerprinting and GPS correlation analysis in advance during map creation, storing processed results for quick retrieval. By pre-processing signal data and establishing baseline correlations between fingerprint data and GPS positions, the system avoids real-time heavy processing during actual navigation, reducing delays while maintaining reliability.
Solution Approach 2:
The system creates simplified positioning maps that copy and store pre-processed positioning information for trusted-GPS regions. Instead of processing raw wireless signal data in real-time, the system uses pre-computed positioning maps that contain correlated fingerprint and GPS data, enabling fast positioning decisions without repetitive heavy processing.
3Measurement precision
If comprehensive data fusion processing is performed to achieve accurate indoor positioning, then positioning accuracy is improved, but device resource usage increases causing power consumption and processing overhead
Solution Approach 1:
The system applies different processing quality levels in different spatial regions. In trusted-GPS zones, it uses simplified GPS-based positioning with minimal data fusion, conserving device resources. In non-trusted zones, it activates full fingerprint-based data fusion for accurate positioning. This localized quality adjustment ensures accuracy where needed while minimizing energy consumption overall.
Solution Approach 2:
The system performs partial data fusion only when necessary - specifically, it combines GPS and fingerprint data only in regions where GPS reliability is questionable or during transition zones. In trusted-GPS regions, it uses GPS alone, and in non-trusted regions, it relies on fingerprint data alone, avoiding the continuous overhead of comprehensive data fusion while maintaining sufficient accuracy.
Data Source
AI summary
A method and system for deploying a trusted-global positioning system (trusted-GPS) positioning map. The method comprises receiving, at a memory of the server computing device, at least a first set of fingerprint data and at least a first set of GPS position data for a sequence of positions traversed within an indoor area by at least a first mobile device, generating, using the processor, a distribution of positioning data points of the indoor area for which a correlation between the at least a first set of fingerprint data and the at least a first set of GPS position data for respective ones of the sequence of positions exceeds a threshold correlation value, and when the distribution exceeds at least one of a predetermined and a dynamically updated threshold density of positioning data points, deploying the distribution as the trusted-GPS positioning map of the indoor area.