Analytic Server Wireless Signal Hypercluster Geolocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for locating lost electronic devices are often tied to specific hardware and software applications, lack accuracy, especially in tall buildings, and are vulnerable to active attacks that can spoof geolocation and signal environments.
Innovation Solution
An analytic server monitors wireless signals from multiple devices, builds signal graphs, generates hyperclusters, and determines geolocation by analyzing observations from observer devices, while also combating active attacks by using historical patterns to verify the authenticity of device locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional geolocation methods are used to locate lost devices, then the device location can be reported, but the accuracy is insufficient for tall buildings and complex environments
Solution Approach 1:
The patent segments the location determination process into multiple components: geolocation data from GPS, semantic resolution data from signal environment analysis (hyperclusters), and historical pattern data. By dividing the location problem into these segments and combining them, the system achieves accurate floor-level and room-level location determination in tall buildings where conventional single-method geolocation fails
Solution Approach 2:
The patent adds semantic dimensions to traditional geolocation by analyzing signal environments (hyperclusters of wireless signals). Instead of relying solely on latitude/longitude coordinates, the system incorporates semantic information about the signal environment to resolve locations to specific floors and rooms, effectively adding vertical and spatial dimensions to the location data
2Reliability
If conventional location tracking systems are implemented, then device location can be determined, but the system is vulnerable to active attacks that can spoof geolocation and signal environments
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring signal environments and comparing them against historical patterns. When a device reports a location, the system feeds back verification by checking whether the reported signal environment matches the expected hypercluster for that location, and whether it aligns with historical patterns, thereby detecting and rejecting spoofed location data
Solution Approach 2:
The system performs preliminary analysis of signal environments and historical patterns before final location determination. By pre-establishing baseline signal environments for different locations and analyzing historical device patterns, the system is prepared to quickly verify or reject reported locations, preventing successful spoofing attacks
3Adaptability or versatility
If manufacturer-specific hardware or applications are required for device location, then location service can be provided, but the system lacks versatility across different devices
Solution Approach 1:
The patent creates a universal location determination system that works across different device types and manufacturers. By using standard wireless signal environments (Wi-Fi, Bluetooth, cellular signals) that all devices emit or detect, and by analyzing these signals through a common hypercluster framework, the system provides location services for any device without requiring manufacturer-specific hardware or applications
Data Source
AI summary
Disclosed herein are embodiments of systems, methods, and products comprise an analytic server, which tracks and locates electronic devices (e.g., wireless devices and devices enabled with wireless transmitters). The analytic server monitors wireless signals detected by different observer devices at different time points. The analytic server analyzes the wireless signals to build signal graph and generate hyperclusters. When the analytic server receives a request of finding a lost/missing device, the analytic server receives observations from observer devices that detect the wireless signals from the missing device, determine signal context (e.g., hypercluster) and geolocation of the missing device based on observations from observer devices, performs resolution to narrow down the geolocation. The analytic server also combats different forms of active attacks. The analytic server generates a graphical user interface comprising the location information of the missing device.