Geofence Exit Monitoring Using Wireless Processor
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Solution Overview
Problem
Conventional mobile devices require constant or frequent location identification to monitor geofences, which consumes significant battery power, as this task is typically performed by the power-hungry application processor.
Innovation Solution
The mobile device uses a wireless processor, such as a WiFi chip, to monitor selected wireless access points, allowing the application processor to remain in an inactive state until a location change is detected, thereby reducing power consumption and enabling efficient geofence monitoring with limited scanning capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the application processor performs constant location identification to monitor geofences, then geofence monitoring accuracy is improved, but battery power consumption increases
Solution Approach 1:
The patent introduces wireless access points as intermediary objects for geofence monitoring. Instead of the application processor directly performing location identification, the system uses wireless access points as mediators to detect device location changes. The wireless processor monitors signals from these access points, serving as an intermediary that enables accurate geofence detection without requiring the application processor to continuously calculate location, thus reducing power consumption while maintaining monitoring accuracy.
Solution Approach 2:
The patent replaces the traditional mechanical/computational approach (application processor performing triangulation or GPS calculations) with a signal-based detection method. The wireless processor detects changes in wireless access point signals to infer location changes, substituting the computationally intensive mechanical calculation process with a more energy-efficient signal monitoring approach. This substitution allows the system to achieve the same geofence monitoring function with significantly reduced power consumption.
2Measurement precision
If the application processor continuously monitors location, then location identification accuracy is improved, but device complexity and processing load increase
Solution Approach 1:
The patent extracts the location monitoring function from the application processor and assigns it to the wireless processor. By separating this function, the application processor is relieved of continuous location calculation tasks, reducing its processing load and complexity. The wireless processor handles the monitoring of access point signals independently, enabling location identification without burdening the main application processor, thus reducing overall system complexity while maintaining accuracy.
Solution Approach 2:
Wireless access points serve as intermediaries that simplify the location determination process. Instead of the application processor directly performing complex triangulation or GPS calculations, it receives indirect location information through wireless processor monitoring of access point signals. This intermediary approach reduces the computational complexity of the application processor while maintaining location identification accuracy through the structured signal-based detection method.
3Adaptability or versatility
If multiple geofences are monitored simultaneously, then monitoring coverage is improved, but power consumption and processing load increase
Solution Approach 1:
The wireless processor is designed to perform multiple geofence monitoring functions simultaneously through a unified signal monitoring approach. By monitoring wireless access point signals, the system can determine location changes relative to multiple geofences at once without requiring separate processing for each geofence. This multi-functional capability allows the system to expand monitoring coverage to multiple geofences while keeping power consumption relatively low, as the same wireless monitoring infrastructure serves all geofence detection needs.
4Measurement precision
If the wireless processor monitors wireless access points frequently, then geofence detection accuracy is improved, but scanning capacity limitations are exceeded
Solution Approach 1:
The system monitors only the necessary wireless access point signals required for geofence detection rather than performing exhaustive scanning of all available wireless signals. By selectively monitoring specific access points that are relevant to the geofence boundaries, the system achieves sufficient detection accuracy without exceeding the wireless processor's scanning capacity. This partial monitoring approach focuses computational resources on the most critical signals, enabling accurate geofence detection within the constraints of limited scanning capacity.
Data Source
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AI summary
Methods, program products, and systems for monitoring geofence exits using wireless access points are disclosed. In general, in one aspect, a mobile device can detect one or more entry gateways that are wireless access points selected for monitoring a geofence. The mobile device can determine that the mobile device is located in the geofence based on the detection. The mobile device can monitor the entry gateways and one or more exit gateways, which can be wireless access points observable by the mobile device when the mobile device is in the geofence. When the mobile device determines, after a number of scans using a wireless processor, that the entry gateways and exit gateways are unobservable, the mobile device can use an application processor to determine whether the mobile device has exited from the geofence.