Automatic Location Tagging via Proximity Detection
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Solution Overview
Problem
Current location tagging techniques in mobile devices require manual input, leading to missed location data storage if users forget to tag their location manually.
Innovation Solution
A method and system utilizing a short-range proximity detector, such as NFC or Bluetooth, to automatically store position data when two mobile devices are brought into close proximity, enabling automatic location tagging and facilitating navigation back to the tagged location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual input is required for location tagging, then user control over location storage is maintained, but location data may be missed if users forget to tag manually
Solution Approach 1:
The system performs location tagging automatically without requiring user action. The mobile device monitors proximity to the point of interest and autonomously stores location data when the device enters and exits the geographic fence, eliminating the need for manual user input while ensuring reliable location tagging.
Solution Approach 2:
The system continuously monitors the device's location against predefined geographic fences and provides feedback by automatically triggering location storage events when boundary conditions are met. This closed-loop monitoring ensures location data is captured reliably based on actual spatial conditions rather than user memory.
2Reliability
If automatic location tagging is implemented, then location data storage reliability improves, but device complexity increases due to additional sensors and processing
Solution Approach 1:
The system leverages the mobile device's existing GPS receiver and processor for location tagging, repurposing components already designed for navigation and location-based services. By making these existing components serve the additional function of automatic location tagging, the system avoids adding dedicated sensors while achieving reliable automatic tagging.
Solution Approach 2:
The system uses the device's existing location determination capabilities to create a virtual model of the device's spatial relationship to points of interest. By copying and processing location data that already exists in the system, rather than requiring new sensing hardware, the implementation maintains simplicity while achieving automatic tagging functionality.
3Measurement precision
If continuous location monitoring is performed, then automatic location tagging accuracy improves, but energy consumption increases
Solution Approach 1:
Instead of continuous monitoring, the system uses periodic location checks triggered by geographic fence boundary crossings. The GPS receiver remains active but location processing is event-driven, occurring only when the device enters or exits predefined zones. This approach maintains tagging accuracy while significantly reducing the average power consumption compared to continuous location analysis.
Solution Approach 2:
The system pre-defines geographic fences around points of interest before the user begins moving. This preliminary setup allows the device to use efficient location sampling and only trigger full location tagging processing when boundary conditions are met, rather than continuously analyzing location data. The pre-established geographic boundaries enable energy-efficient event-driven processing.
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
Enables seamless and automatic location tagging, ensuring that location data is stored without user intervention, and provides efficient navigation instructions to return to the tagged location, enhancing user experience by eliminating the need for manual input.
Implementation Method 1
the short-range proximity detector may comprise a near field communications (NFC) interface
Implementation Method 2
Other short-range wireless technologies, e.g. Bluetooth® may be utilized
Data Source
AI summary
A method of tagging a location using a mobile device entails obtaining position data for a current location of the mobile device, detecting a proximity of another device using a short-range wireless interface, and automatically storing the position data for the current location of the mobile device in response to the detecting of the proximity of the other device. The proximity detector may comprise a near field communication (NFC) interface, a Bluetooth® transceiver or another short-range wireless technology that may be employed to detect the proximity of another device. This technology enables two devices to store a current location to facilitate a subsequent rendezvous back at that same location.