Indoor Navigation Map Generation Using Mobile Device Location Clustering
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Solution Overview
Problem
Navigation systems face challenges in determining navigation directions within indoor environments without a corresponding map or grid of structural elements, as they cannot accurately identify points of interest or corridors based solely on available electronic maps.
Innovation Solution
The system correlates location estimates from mobile devices in time and space to infer points of interest and corridors, using clustering and vector analysis to determine stationary and moving users, thereby generating an electronic map with annotated points of interest and travel routes even without pre-existing map data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If navigation systems use pre-existing maps with structural elements, then navigation accuracy is improved, but adaptability to new or unknown indoor environments deteriorates
Solution Approach 1:
The system performs preliminary actions by collecting location estimates from mobile devices before actual navigation occurs. These location data are stored and processed to create or update electronic maps in advance, enabling accurate navigation without requiring pre-existing detailed maps of the specific indoor environment.
Solution Approach 2:
The navigation system serves itself by automatically generating and updating electronic maps using location data collected from users' mobile devices. The system processes this data to identify points of interest, corridors, and spatial relationships, creating a self-updating map database that adapts to unknown environments without external intervention.
2Ease of operation
If navigation systems rely on known structural elements, then route determination is improved, but ability to operate in unfamiliar indoor areas deteriorates
Solution Approach 1:
The system uses an intermediary approach by introducing mobile devices as data collection mediators. These devices gather location estimates that serve as intermediaries between users and the navigation system, enabling the system to infer structural elements and create navigation routes in unfamiliar areas without direct knowledge of the environment's physical layout.
Solution Approach 2:
The patent replaces traditional mechanical mapping approaches (relying on physical surveying or pre-printed maps) with electronic data processing. Location estimates from mobile devices are processed through computational algorithms to generate electronic maps and navigation routes, substituting manual or pre-existing mechanical mapping methods with automated electronic systems.
3Measurement precision
If the system collects location estimates from multiple mobile devices, then map accuracy is improved, but data processing complexity increases
Solution Approach 1:
The system applies segmentation by dividing the complex task of processing multiple location estimates into separate functional modules: collecting location data from mobile devices, processing and correlating this data to identify patterns, and generating final map representations. This modular approach manages complexity by handling data processing in discrete, manageable stages rather than as a monolithic complex system.
Data Source
AI summary
The subject matter disclosed herein relates to a system and method for identification of points of interest within a predefined area. Location estimates for substantially stationary mobile devices may be utilized to determine locations of one or more points of interest. Location estimates for mobile devices in motion may be utilized to determine locations of one or more corridors.