Wireless Scan Data Venue Identification
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Solution Overview
Problem
Existing location-based services face challenges in accurately identifying specific venues using geographic coordinates, which can include multiple points of interest, and require resource-intensive GPS data collection, leading to potential inaccuracies due to signal noise.
Innovation Solution
A computer-implemented method that directly maps wireless scan data, such as MAC addresses, to venues using active validation data and historical wireless scan data, allowing for the ranking of potential venues based on likelihood, thereby predicting the exact venue without relying on geographical coordinates and minimizing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If geographic coordinates are used to identify venues, then location-based services can provide venue information, but the accuracy is reduced because geographic coordinates can include multiple points of interest
Solution Approach 1:
The patent introduces wireless access point identifiers (MAC addresses, BSSIDs) as an intermediary between geographic coordinates and venue identification. Instead of directly mapping coordinates to venues, the system uses wireless signal identifiers as a mediating layer that provides more granular venue-specific identification, resolving the ambiguity of coordinates that cover multiple points of interest
Solution Approach 2:
The patent replaces the GPS-based mechanical location system with a wireless signal-based identification system. By substituting satellite-based geographic coordinates with locally-generated wireless access point identifiers, the system achieves more precise venue identification without relying on the less precise coordinate-based approach
2Measurement precision
If GPS data collection is used for location-based services, then venue location can be determined, but resource consumption increases due to the resource-intensive nature of GPS data collection
Solution Approach 1:
The patent enables processing devices to self-determine venue location by scanning and analyzing wireless access point signals in their immediate environment. Instead of relying on resource-intensive GPS satellite communications, devices use low-power wireless scanning to identify venues through locally-available access point identifiers, making the system energy-efficient and self-sufficient
Solution Approach 2:
The patent replaces expensive, resource-intensive GPS data collection with cheap, readily-available wireless signal data. Wireless access point identifiers are freely transmitted by access points and can be scanned by any device with a wireless interface, providing a low-cost alternative to GPS that consumes minimal energy
3Measurement precision
If GPS data collection is used for venue identification, then location can be determined, but inaccuracies occur due to signal noise
Solution Approach 1:
The patent uses wireless access point identifiers as an intermediary that is less susceptible to signal noise than GPS data. These identifiers provide stable, discrete signals that can be reliably detected and matched to venues, avoiding the continuous analog nature of GPS signals that are prone to noise and interference
Solution Approach 2:
The patent substitutes the GPS signal-based location determination with wireless access point signal-based identification. This replacement eliminates dependence on satellite signals that are vulnerable to atmospheric interference and multipath effects, using instead locally-generated wireless signals that are more resistant to noise
Data Source
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AI summary
In non-limiting examples, wireless scan data collected from a processing device is directly mapped to venues. Wireless scan data is received from a processing device where the wireless scan data comprises at least a first identifier of a wireless connection. Venues associated with the first identifier are identified from a mapping of wireless identifiers to venues based on active validation data associated with particular venues including historical wireless scan data of the particular venues. The plurality of venues are ranked according to a likelihood that the processing device is located at a particular venue based on evaluating the active validation data including the historical wireless scan data from the mapping. A predicted venue that the processing device is located at is determined based on the ranking of the plurality of venues. Other examples are also described.