Mobile Device Location Accuracy via Proximity Detection
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Solution Overview
Problem
Current location detection methods for mobile communication devices, such as network-based triangulation and GPS, lack accuracy and efficiency in collecting and reporting location data for a high volume of devices, especially in crowd sensing applications.
Innovation Solution
Equipping mobile communication devices with location-tracking and presence-sensing capabilities, using GPS for accurate self-location determination and short-range radio signals like Bluetooth, NFC, and WiFi to detect and report the locations of nearby devices, enabling simultaneous collection and reporting of location data with high accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network-based triangulation is used to determine location, then a high volume of mobile communication devices can be located, but location accuracy deteriorates to 100+ meters
Solution Approach 1:
The patent combines network-based location determination with device-to-device proximity detection. Each mobile device determines its own location using network-based methods while simultaneously detecting nearby devices through short-range radio signals. This merging allows the system to maintain high volume processing capability while improving accuracy through multiple detection mechanisms working together.
Solution Approach 2:
The patent introduces an intermediary approach where mobile devices themselves participate in the location detection process by detecting presence of nearby devices through short-range radio signals. This intermediary mechanism (device-to-device detection) supplements the traditional network-based approach, enabling improved accuracy without sacrificing the ability to handle high volumes of devices.
2Measurement precision
If GPS is used by each mobile device to determine location, then location accuracy improves to approximately 10 meters, but the complexity and resource consumption increase
Solution Approach 1:
The patent applies partial action by having each mobile device perform only the necessary location determination functions rather than requiring full GPS functionality on all devices. Devices use their existing location capabilities combined with simple proximity detection mechanisms, avoiding the excessive complexity of implementing complete GPS systems on every device while still achieving high accuracy.
Solution Approach 2:
The patent implements self-service by enabling each mobile device to autonomously determine its own location and detect nearby devices without requiring centralized coordination or complex system infrastructure. Each device uses its own resources (location services, radio signal detectors) to perform the detection function, reducing overall system complexity while maintaining high accuracy.
3Measurement precision
If device-to-device proximity detection is implemented, then location accuracy improves, but the quantity of devices that can be simultaneously tracked decreases
Solution Approach 1:
The patent segments the location detection task into two parts: (1) network-based location determination for each device, and (2) device-to-device proximity detection for nearby devices. This segmentation allows the system to handle large numbers of devices through network-based methods while simultaneously providing high accuracy through localized device-to-device detection for nearby devices.
Solution Approach 2:
The patent applies local quality by providing high-accuracy location determination through device-to-device detection only for nearby devices within proximity, while using less resource-intensive network-based methods for all devices. This localized approach to high-precision detection maintains the ability to track large numbers of devices while improving accuracy where most needed (for nearby devices).
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 approach allows for accurate and efficient collection and reporting of location data for a large number of devices, improving accuracy from 100+ meters to approximately 10 meters, and enables effective analytics for crowd size estimation and traffic flow analysis.
Implementation Method 1
determining a location of the first mobile communication device
Implementation Method 2
detecting presence of a second mobile communication device located within a proximity of the first mobile communication device
Data Source
AI summary
A mobile communication device collects and reports location data associated with itself and with mobile communication devices within a proximity. The mobile communication device determines its location and detects the presence of another communication device located within the proximity of the mobile communication device. The mobile communication device determines a location of the other mobile communication device. The mobile communication device reports its location and the location of the other mobile communication device.


