Subway Transit Location Analysis Using Cell Site and WiFi Data
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Solution Overview
Problem
In subway environments, the lack of radio coverage for mobile communication devices hinders the collection of location data, making it difficult to infer user locations and transit routes, which is crucial for understanding traffic patterns and optimizing subway system operations.
Innovation Solution
A method and system that analyze location data from mobile communication devices using cell site identities and WiFi access point signatures to determine entry and exit points in the subway system, inferring probabilities of different transit routes and calculating traffic at points-of-interest by attributing fractional credits based on statistical analysis of device transits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If location data is collected using mobile communication devices in subway environments, then traffic pattern analysis can be performed, but radio coverage is lost underground making location data collection difficult
Solution Approach 1:
The patent uses subway station entrances and exits as intermediary points to bridge the radio coverage gap. Location data is collected at these transition points where devices move between above-ground (with radio coverage) and below-ground (without radio coverage) areas, enabling indirect tracking of subway transit routes
Solution Approach 2:
The patent replaces direct radio-based location tracking with a statistical inference system that uses cell site identity and WiFi access point data collected at station entrances/exits to probabilistically determine transit routes and traffic patterns
2Adaptability or versatility
If multiple subway routes are considered for analysis, then route probability inference is possible, but data processing complexity increases
Solution Approach 1:
The patent segments the subway system into discrete entry points, exit points, and routes. By dividing the complex transit network into manageable segments with defined characteristics, the system can process multiple routes systematically using statistical models without overwhelming computational complexity
Data Source
AI summary
A method of determining traffic in a subway system. The method comprises analyzing a first type of location data associated with mobile communication devices to determine subway entry points and subway exit points of the devices, analyzing different pairs of entry and exit points to infer probabilities that a device transits between a pair of entry points by different routes based on a WiFi SSID included in the first type of location data, analyzing a second type of location data associated with mobile communication devices to identify entry and exit points of the devices based on a cell site identity included in the second type of location data, for each pair of entry point and exit point associated with the second type of location data, determining a fractional route count for the device transiting between the entry and exit points for each different subway route based on the inferred probabilities.


