Network Presence Sensing Using Signal Scatter for Human Tracking
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Solution Overview
Problem
Existing object tracking systems, particularly Network Presence Sensing (NPS) systems, face challenges with high computational demands and resource overhead, limiting their applicability and accuracy, especially when fiducial elements are not used or misplaced, and require significant training time.
Innovation Solution
A method that combines signal absorption and forward scatter analysis in a wireless communications network to detect biological masses, such as humans, without relying on fiducial elements, using transceivers to create baseline signal profiles and compare them with new signal data for object detection and tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Network Presence Sensing systems use signal analysis to detect and track objects, then tracking capability is improved, but computational loading and resource requirements increase
Solution Approach 1:
The system performs preliminary actions by creating baseline signal profiles during a training phase before actual tracking begins. These baselines capture the characteristic signal absorption and forward scatter patterns of different object types. During operation, the system compares new signal data against these pre-established baselines, avoiding the need for complex real-time analysis and reducing computational loading while maintaining reliable tracking capability.
2Measurement precision
If NPS systems perform comprehensive signal analysis to distinguish object types, then measurement precision is improved, but time consumption and training requirements increase
Solution Approach 1:
The system extracts and utilizes specific, distinguishing characteristics from the signal data - namely signal absorption patterns and forward scatter characteristics. By focusing only on these key differentiating features rather than analyzing all signal parameters comprehensively, the system achieves accurate object differentiation while reducing the time required for training and operation.
3Measurement precision
If fiducial elements are used for object tracking, then location accuracy is improved, but device complexity and overhead increase
Solution Approach 1:
The system enables objects to be tracked through their inherent physical properties - specifically their natural signal absorption and forward scatter characteristics - without requiring them to carry or wear fiducial elements. The objects essentially track themselves by their interaction with the wireless signals in the environment, eliminating the need for additional tracking devices and reducing system overhead while maintaining location accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Reduces computational loading and enhances tracking accuracy by leveraging existing network signals to differentiate between humans and other objects, allowing for real-time detection and location estimation with reduced resource requirements.
Implementation Method 1
The primary NPS systems and methods for doing such tracking herein are described in U.S. Pat. Nos. 10,064,013 and 9,693,195... use signal absorption, as well as signal forward scatter and reflected backscatter of the RF communication
Implementation Method 2
use signal absorption, as well as signal forward scatter and reflected backscatter of the RF communication
Data Source
AI summary
Systems and methods for detecting the presence of a body (typically a human) in a network without fiducial elements while additionally using fiducial elements to assist the system and possibly reduce the computational loading on the system. The fiducial element may be used in many ways including, without limitation, assisting in ignoring some bodies present in the detection area and training the system using additional data.