Wireless Fingerprint User Tracking in Indoor Spaces
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Solution Overview
Problem
Existing location tracking systems, particularly in indoor environments, face inaccuracies and unavailability due to GPS limitations, and conventional wireless fingerprint methods cannot triangulate user locations, making it difficult to determine user interactions and geographic spaces effectively.
Innovation Solution
The system utilizes wireless fingerprint information to track user interactions by correlating proximity records based on time and user information, clustering these records to identify events and geographic spaces, and outputs relevant information, including user interaction profiles and space occupancy, using a network environment with wireless access points and a server system to process and analyze wireless fingerprints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS is used for location tracking, then outdoor location accuracy is achieved, but indoor and obstructed environment tracking becomes unavailable or unreliable
Solution Approach 1:
The patent introduces WiFi access points as intermediary objects to enable location tracking in environments where GPS is unavailable. Instead of directly using GPS satellites, the system mediates location determination through local WiFi infrastructure, allowing continuous tracking both indoors and outdoors by switching between these positioning methods.
2Measurement precision
If WiFi fingerprinting is used to improve indoor location accuracy, then location precision increases, but the ability to triangulate user locations is lost
Solution Approach 1:
The patent merges WiFi fingerprinting technology with proximity record analysis to combine the advantages of both approaches. WiFi fingerprints provide accurate indoor location identification, while the system simultaneously maintains proximity records that enable triangulation-like analysis of user interactions and spatial relationships, thus preserving spatial reasoning capabilities while achieving precise indoor positioning.
3Loss of information
If proximity records are collected for all user interactions, then complete user relationship data is obtained, but data processing complexity increases
Solution Approach 1:
The patent segments the large set of proximity records into meaningful clusters representing different user interactions and events. By dividing the comprehensive proximity data into organized clusters based on temporal and spatial patterns, the system maintains complete user relationship information while reducing processing complexity through structured data organization and pattern recognition.
Data Source
AI summary
Methods, systems, and articles of manufacture for tracking users based upon wireless fingerprint information are provided. These include accessing proximity records, clustering the proximity records based upon time information and user information to generate a plurality of clusters, identifying one or more events based upon the generated clusters, and outputting information related to the identified one or more events. Each proximity record includes user information. User information includes at least a first user identifier and a second user identifier respectively identifying a first user and a second user, and time information. Time information specifies one or more times when the first user and the second user have respective wireless fingerprints that are within a threshold fingerprint distance of each other.