Crowd-Sourced Pathway Maps Using Signal Strength Trends
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Solution Overview
Problem
Indoor location-based services face challenges in obtaining prior knowledge of building layouts, as floor plans are often proprietary, outdated, or difficult to acquire, making it costly for service providers to offer their services, especially in legacy buildings or shopping centers.
Innovation Solution
A system that uses mobile devices with IMU sensors and wireless signal strength analysis to identify device-perceived landmarks, which are then used by a server system to generate pathway maps without requiring explicit floor plans, by leveraging trends in received signal strength and inertial measurement data from multiple devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If service providers acquire floor plans or perform onsite surveys to provide indoor location-based services, then service accuracy is improved, but cost and complexity increase significantly
Solution Approach 1:
The system enables users to automatically contribute pathway map data through their mobile devices without requiring service provider intervention. Mobile devices autonomously collect signal strength data, identify landmarks, and submit contributions to the server system, eliminating the need for expensive provider-conducted surveys while improving service accuracy through crowd-sourced data
Solution Approach 2:
The patent replaces traditional mechanical surveying methods (onsite surveys by service providers) with an electronic signal-based system. Mobile devices use wireless signal strength measurements and IMU sensor data to automatically generate pathway maps, substituting expensive human surveyors with automated electronic data collection and processing
2Measurement precision
If service providers obtain proprietary floor plans from building owners, then mapping accuracy is improved, but ease of operation deteriorates due to opt-in requirements
Solution Approach 1:
Instead of requiring building owners to provide floor plans to service providers, the system inverts the approach: mobile devices independently generate pathway maps from signal strength data and contribute them directly to the server system. This eliminates the opt-in barrier while maintaining mapping accuracy through automated landmark identification and pathway reconstruction
Solution Approach 2:
The system creates functional copies of floor plan information without requiring original proprietary documents. Mobile devices generate pathway maps that replicate the navigational information contained in floor plans by identifying landmarks and reconstructing pathways from signal strength variations, providing equivalent functionality without legal or operational barriers
3Measurement precision
If crowd-sourced data from multiple mobile devices is collected and processed, then pathway map accuracy is improved, but data processing complexity increases
Solution Approach 1:
The server system merges data from multiple mobile devices by identifying common landmarks and integrating their respective pathway contributions. By combining signal strength data and landmark identifications from numerous devices, the system reconstructs comprehensive pathway maps with improved accuracy through aggregated crowd-sourced information
Solution Approach 2:
The server system acts as an intermediary that receives, processes, and integrates data from multiple mobile devices. It mediates the complex task of combining crowd-sourced data by matching landmarks across different device contributions and synthesizing unified pathway maps, simplifying the data processing complexity through centralized coordination
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables the creation of accurate pathway maps without prior knowledge of building layouts, reducing costs and complexities for service providers, while providing stable and consistent reference points for indoor location-based services.
Implementation Method 1
the mobile device monitors a trend in the received signal strength of the wireless signal from the wireless access point as the mobile device is moved
Implementation Method 2
inertial measurement unit (IMU) sensors (electronic sensors that measure and monitor velocity, orientation, and gravitational forces, such as accelerometers, magnetometers, gyroscopes and GPS)
Data Source
AI summary
Some implementations include identifying a location for a device perceived landmark. The location is identified by monitoring received signal strength of a signal of a wireless access point, detecting the location at which the trend in the received signal strength changes direction, and qualifying the location based on measurements taken form one or more inertial measurement unit sensors.