Wireless Sensing Subject Identification via Segmentation
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Solution Overview
Problem
Current wireless communication systems face limitations in accurately identifying subjects within a sensing area through device-free sensing approaches, particularly in determining whether a subject is known or unknown and associating them with authorized devices based on wireless environment data.
Innovation Solution
A method that analyzes wireless environment data from a pair of wireless devices to determine subject motion, involving three determinations: whether the subject's media protocol address is new and uncorrelated, known and correlated, or unassociated with any device, to perform appropriate actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If device-free sensing approaches are used to detect human motion, then motion detection capability is improved, but subject identification accuracy deteriorates
Solution Approach 1:
The system segments the identification process into three distinct determination stages: (1) checking if the subject's device is new and uncorrelated, (2) checking if the subject's device is known and correlated, and (3) determining if the subject is unassociated with any device. This segmentation allows the system to handle different identification scenarios systematically, improving both motion detection and identification accuracy.
Solution Approach 2:
The system performs preliminary actions by maintaining stored data of known devices and their correlations before subject identification occurs. When motion is detected, the system immediately compares the detected device against pre-stored data, enabling rapid and accurate identification without requiring real-time analysis of all possible devices.
2Measurement precision
If wireless environment data is analyzed to identify subjects, then subject identification capability is improved, but system complexity increases
Solution Approach 1:
The identification process is divided into three clear determination steps with distinct decision criteria. Each step checks specific conditions (new/uncorrelated, known/correlated, unassociated) and leads to different actions. This segmentation reduces system complexity by providing a structured decision framework that is easier to implement and maintain.
Solution Approach 2:
The system performs only the necessary determinations needed for identification rather than analyzing all possible wireless parameters. By focusing on specific aspects of wireless environment data relevant to device recognition and correlation, the system achieves effective subject identification without unnecessary complexity.
3Measurement precision
If multiple determinations are performed to classify subjects, then identification accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary preparation by storing device data and correlation information before identification is needed. When motion is detected, the system immediately compares against pre-stored data, significantly reducing processing time while maintaining high identification accuracy through the three-determination framework.
Solution Approach 2:
The system performs a limited set of three specific determinations rather than comprehensive analysis. Each determination checks specific conditions and leads to actionable conclusions, enabling rapid processing while maintaining high identification accuracy through focused analysis of critical parameters.
Data Source
AI summary
The systems and method proposed herein aim to identify a mobile device or devices worn by an individual or a subject that has entered an area monitored by a passive motion detection system that uses wireless signals to sense motion in the space. The system will collect as much signals as possible from both the devices worn by the individual and from the system performing the passive (device-free) motion detection for identifying the individual or person of interest. The individual or person of interest may be a user of a product or an intruder.