WiFi Mesh Network for Anonymous Traffic Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for tracking the motion and trajectory of objects with wireless communication devices within predefined areas are complex, costly, and do not effectively provide reliable, anonymous traffic analysis and statistics, especially concerning passenger and motor vehicle traffic distribution.
Innovation Solution
A passive method utilizing a mesh network of intelligent WIFI access points to estimate device location and movement speed without requiring active device participation, using signal strength measurements and machine learning models for anonymous data processing and analysis in a Peer-to-Peer (P2P) system, minimizing central server involvement and protecting personal data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized server means are used for data collection and analysis, then comprehensive traffic analysis can be performed, but system complexity and cost increase
Solution Approach 1:
The patent divides the centralized server system into distributed intelligent access points that independently perform data collection, processing, and analysis. Each access point segments the overall traffic analysis function, eliminating the need for a complex centralized server while maintaining comprehensive analysis capabilities through local peer-to-peer communication.
Solution Approach 2:
The intelligent access points are designed to autonomously collect WiFi signal data, process traffic information, and perform analysis without requiring centralized server control. Each access point serves itself by locally executing traffic monitoring and analysis functions, reducing system complexity and cost while maintaining reliability.
2Measurement precision
If active device participation is required for tracking, then accurate motion data can be obtained, but user privacy and data protection concerns increase
Solution Approach 1:
The patent introduces WiFi signal strength measurements as an intermediary that indirectly captures motion information without requiring direct device participation or access to personal data. The signal strength serves as a mediator that provides motion tracking accuracy while preserving user privacy, as it does not require devices to actively transmit location information.
Solution Approach 2:
The patent replaces active device participation (mechanical/systematic device cooperation) with passive WiFi signal field measurements. Instead of requiring devices to actively report location data, the system uses electromagnetic field signal strength variations to infer motion, thereby maintaining measurement precision while eliminating personal data exposure risks.
3Reliability
If special tracking codes are installed on devices, then reliable traffic monitoring is achieved, but device complexity and implementation cost increase
Solution Approach 1:
The patent leverages the self-service capability of WiFi clients that automatically perform signal scanning and connection attempts. Devices naturally emit WiFi client signals without requiring special tracking codes or modifications, enabling reliable traffic monitoring while maintaining ease of implementation across standard devices.
Solution Approach 2:
Instead of requiring special tracking codes on each device, the patent copies and analyzes the naturally occurring WiFi client signals that all modern devices already emit. This approach achieves reliable traffic monitoring by utilizing existing device functionality rather than requiring additional hardware or software modifications.
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
This method provides reliable, universal, and cost-effective analysis of traffic intensity and direction, enabling comprehensive traffic reviews while maintaining anonymity and reducing personal data exposure, by estimating movement types and speeds through local data processing and P2P communication.
Implementation Method 1
Based on the signal strength of the WIFI client measured at access points, it is possible to estimate its distance from one or more measuring points
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method for tracking the movement and trajectory of objects associated with wireless devices, located in a predefined area, whereas transceiver nodes communicating with the monitored wireless communication devices are formed in a predefined area and the objects associated with wireless communication device entering or located in the range of the transceiver nodes are detected by said transceiver nodes. At least one element of the data group comprising the fact of the detection, the number of the detected objects and the trajectory of the detected moving objects is stored, and the stored information is made available for further processing. Access points functioning according to a small-range wireless communication standard are used as transceiver nodes and are installed relative to each other at a distance suitable for carrying out wireless communication with each other; "peer-to-peer" (P2P) type communication is carried out between the access points, and the position of the monitored object in the range of at least two access points is defined by the access points with a resolution exceeding that of the detection mesh network formed by the access points, comprising - measuring the strength of the signal emitted by the object during communication by at least two access points, - converting the measured signal strength data into a vector set, - selecting and filtering out the objects that are communicating but make no movement by evaluating the vector set, and - analysing the movement of the communicating objects changing their place by applying a pre-defined mathematical model.