Mobile Device Detection via Distributed Tracking Framework
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Solution Overview
Problem
Existing wireless networks do not provide additional benefits to users, as they cannot enhance user experience through detection of mobile devices or their unique identifiers.
Innovation Solution
A system that detects mobile devices and identifies users by associating their wireless signatures or unique identifiers with user information, allowing for personalized offers and services based on location and user data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If wireless access points detect mobile devices and their unique identifiers, then device detection capability is improved, but user experience enhancement remains insufficient
Solution Approach 1:
The patent introduces a server as an intermediary component that receives device identification data from access points, processes this information, and generates personalized offers. This intermediary enables the system to transform raw detection capabilities into meaningful user experience enhancements by adding a layer of intelligent processing between detection and user interaction.
Solution Approach 2:
The system performs preliminary actions by pre-processing device identification data, retrieving user information from databases before the actual interaction occurs. User profiles, preferences, and historical data are prepared in advance so that when a device is detected, personalized offers can be immediately generated and presented, enhancing user experience without requiring real-time processing delays.
2Measurement precision
If user information is associated with mobile devices through secondary sources, then user identification accuracy is improved, but system complexity increases
Solution Approach 1:
The server performs multiple functions within a single system component: it receives device identifiers from access points, queries user information from various data sources (databases, external APIs), processes and matches this information, and generates personalized offers. This multi-functionality consolidates what would otherwise require multiple separate systems into one unified platform, managing complexity while improving identification accuracy.
Solution Approach 2:
The system incorporates feedback mechanisms where user information retrieved from secondary sources is used to refine future identifications and offer generation. The feedback loop allows the system to learn from previous interactions and improve its matching accuracy over time, enhancing identification precision while the automated feedback process manages complexity through algorithmic optimization rather than manual configuration.
3Productivity
If personalized offers are generated based on location and user data, then marketing effectiveness is improved, but data processing requirements increase
Solution Approach 1:
User information is retrieved and processed in advance before the actual marketing interaction occurs. The system pre-queries databases for user profiles, preferences, and historical data associated with detected devices, so that when location-based marketing is triggered, the necessary information is already prepared and can be immediately used to generate personalized offers, reducing real-time processing requirements.
Solution Approach 2:
The system applies local quality by tailoring offers specifically to the detected location and the individual user's preferences rather than using generic mass marketing. The server processes data to create location-specific and user-specific offer variations, optimizing marketing effectiveness for each local context while managing processing requirements by targeting only the necessary data retrieval and processing for each specific user-location combination.
Data Source
AI summary
Systems, methods and computer-readable media for detecting a mobile device and identifying a user of the device are provided. A wireless signature or other unique identifier of a device may be detected. User information for the device may be obtained from a secondary source independent of the mobile device. Once a user is identified, user information may be retrieved and the user identity and user information may be associated with a mobile device. When the mobile device is then detected at a later time (e.g., after the information has been associated with the device), one or more offers may be generated based on the associated information and/or the location of the device at the time it is detected.