Wi-Fi Localization with Auxiliary Sensor Identity Linking
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Solution Overview
Problem
Traditional Wi-Fi localization techniques fail to track mobile devices effectively when their addresses are randomized, leading to double counting or loss of locality in tracking scenarios, due to the non-persistent nature of device addresses.
Innovation Solution
A system and method that utilize auxiliary sensor information, such as video data and proximity between devices, to maintain continuous identity for mobile devices by linking new addresses with previously associated addresses, ensuring uninterrupted tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If device addresses are randomized to protect user privacy, then user privacy is improved, but tracking continuity deteriorates
Solution Approach 1:
The patent introduces auxiliary sensor information (camera images, microphone audio, other sensors) as intermediary data to bridge the gap between randomized device addresses. These sensor data serve as mediators that allow the system to identify and track the same mobile device even when its network address changes, thus maintaining tracking continuity while preserving user privacy through address randomization
Solution Approach 2:
The system changes from relying solely on network address parameters to incorporating multiple sensor-based parameters (visual characteristics from camera, audio signatures from microphone, other sensor readings). This parameter diversification allows continuous device identification regardless of address randomization, resolving the contradiction between privacy protection and tracking reliability
2Device complexity
If traditional Wi-Fi localization techniques are used with randomized addresses, then system simplicity is maintained, but tracking accuracy deteriorates
Solution Approach 1:
The patent merges Wi-Fi localization data with auxiliary sensor information from multiple sources (camera, microphone, other sensors). By combining these different data types, the system achieves more accurate device identification and tracking than traditional Wi-Fi localization alone, while the integration is performed in a way that builds upon existing infrastructure rather than replacing it entirely
3Object-affected harmful factors
If address randomization is implemented, then privacy protection is improved, but analytics reliability deteriorates
Solution Approach 1:
Auxiliary sensor information acts as an intermediary that preserves analytics reliability despite address randomization. By using sensor data (visual, audio, other) as intermediate identifiers, the system can maintain accurate device-level analytics, crowd counting, and location-based services without relying on persistent network addresses
Solution Approach 2:
The system creates alternative identification copies through sensor data. Instead of relying on the original network address as the sole identifier, it generates parallel identification streams from camera images, audio signatures, and sensor readings that can be used to track devices and maintain analytics accuracy even when the primary address identifier is randomized
Data Source
AI summary
In one implementation, a method of maintaining continuous identity for mobile devices includes: obtaining a first address for a first device; and obtaining, from one or more auxiliary sensors, auxiliary sensor information related to the first device. The method also includes determining whether the auxiliary sensor information matches information associated with a second address, where the second address was previously associated with the first device. The method further includes linking the first address with the second address for the first device, in order to continue tracking the first device when the second address is no longer detected, in response to determining that the auxiliary sensor information matches information associated with the second address.