Wireless Device Identification via Camera and Location Data Fusion
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Solution Overview
Problem
In environments where computer vision systems and wireless networks are deployed, there is a challenge in automatically identifying users of wireless devices that have not been previously registered, especially when the computer vision system fails to recognize individuals due to changes in appearance or lack of access to reference representations.
Innovation Solution
An integration system that combines data from wireless location systems and computer vision systems to calculate proximity parameters and probabilities of association between wireless devices and individuals, allowing for automatic registration of unregistered wireless devices by associating them with identified users based on spatial relationships and probability thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If computer vision system is used for user identification, then identification accuracy is improved, but system reliability deteriorates when appearance changes occur or reference representations are unavailable
Solution Approach 1:
The patent introduces wireless device location data as an intermediary to bridge the gap between computer vision identification and wireless network access. When computer vision fails to identify a user (due to appearance changes or lack of reference representations), the system uses the location of wireless devices combined with proximity calculations to infer user identity, thereby maintaining system reliability without sacrificing identification accuracy when vision-based methods succeed
2Ease of operation
If automatic registration of wireless devices is implemented, then ease of operation is improved, but device complexity increases due to integration requirements
Solution Approach 1:
The patent merges computer vision systems, wireless location systems, and network access control into a unified integration system. This consolidation enables automatic registration of wireless devices by combining location data from wireless infrastructure with visual data from cameras, allowing the system to automatically associate users with their devices without requiring manual intervention, thereby improving ease of operation while managing complexity through integrated architecture
3Reliability
If proximity-based association is used to link wireless devices with individuals, then identification reliability is improved, but measurement precision requirements increase
Solution Approach 1:
The patent adds a temporal dimension to the proximity-based association method. Instead of relying solely on instantaneous spatial proximity (which would require high measurement precision), the system tracks location data over time and uses persistence of proximity as a reliability indicator. This temporal aspect allows the system to maintain identification reliability while reducing the stringency of immediate measurement precision requirements
Data Source
AI summary
In one example embodiment, an integration system obtains, based on data from a wireless location system, location data of a wireless device in a spatial area. The integration system determines location data of a person in the spatial area based on at least one image of the person captured by a camera. Based on the location data of the wireless device and the location data of the person, the integration system calculates a proximity parameter representing a spatial relationship between the wireless device and the person. Based on the proximity parameter, the integration system computes a probability of association between the wireless device and the person and determines, based on the probability of association, whether the person is a user of the wireless device.