Dynamic Geofencing for Loitering Detection
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Solution Overview
Problem
Existing location tracking methods consume excessive power and resources due to frequent location polling, and fail to accurately differentiate between temporary passage and loitering at geofenced areas, leading to inaccurate check-in/check-out processes.
Innovation Solution
Implement dynamic geofencing that adjusts geofence size based on device speed and velocity, allowing for less frequent location polling and automatic check-in/check-out verification by determining the duration of presence within a geofenced area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequent location polling is used to track device location, then location tracking accuracy is improved, but power consumption and resource usage increase
Solution Approach 1:
The geofence radius is dynamically adjusted based on the device's speed and velocity. When the device moves faster, the geofence radius increases to reduce polling frequency, while slower movement results in smaller radii and higher polling frequency, optimizing both accuracy and power consumption
Solution Approach 2:
The system changes the geofence radius parameter according to device velocity. By modifying this key parameter based on movement conditions, the system achieves adaptive location tracking that balances accuracy requirements with power consumption constraints
2Device complexity
If fixed geofence size is used, then system complexity is reduced, but ability to differentiate loitering from passage deteriorates
Solution Approach 1:
The geofence transitions from a fixed size to a dynamic size that adapts to device velocity. This dynamic adjustment enables the system to distinguish between devices passing through (higher speed, larger effective coverage) and devices loitering (lower speed, smaller effective coverage), improving detection accuracy without significantly increasing system complexity
Solution Approach 2:
The system pre-calculates appropriate geofence radii based on expected device velocities and movement patterns. By preparing velocity-based radius thresholds in advance, the system can quickly determine loitering status without complex real-time calculations, maintaining low complexity while improving accuracy
3Ease of operation
If device speed is not considered, then check-in process is simplified, but accuracy of check-in/check-out verification deteriorates
Solution Approach 1:
The system automatically incorporates device velocity data into the check-in verification process without requiring additional user input or complex manual verification. The velocity-based geofence radius automatically adjusts to verify legitimate check-ins while filtering out false positives from passing devices, maintaining simplicity while improving reliability
Solution Approach 2:
The system uses device velocity as feedback to dynamically adjust geofence parameters during check-in verification. By continuously monitoring speed and adjusting the effective check-in zone accordingly, the system automatically verifies authentic check-ins while rejecting false ones, enhancing reliability without complicating the user experience
Data Source
AI summary
A location system of a mobile device may detect a first location and a second location of the mobile device. A processor of the mobile device may determine that the first location and second location are within a geofence surrounding the location of interest. The processor may determine a speed at which the mobile device traveled from the first location to the second location. The processor may determine that the mobile device is loitering at the location of interest in response to the speed being below a threshold value. In response to determining that the mobile device is loitering at the location of interest, the processor may perform check in processing to check a user of the mobile device as being on site at the location of interest.