Mobile Geofence Monitoring With Adaptive Ranging and Motion Classifiers
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Solution Overview
Problem
Existing location services for smart devices suffer from low accuracy, high latency, and false positive classifications, which hinder the functionality of smart systems by causing power drain, degraded user experience, and incorrect geo-fence exits.
Innovation Solution
Implementing dynamic algorithms that adjust ranging and sensor rates based on wireless signals, using motion classifiers and geofence adjustments to enhance location accuracy and reduce latency, and employing ultra-wide band protocols for precise distance measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If location services are continuously monitored at high frequency, then location accuracy is improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts the location monitoring frequency based on the device's motion state. When the motion classifier detects that the device is stationary, the ranging rate is reduced or suspended. When motion is detected, the monitoring frequency increases automatically. This dynamic adaptation resolves the contradiction by matching resource consumption to actual operational needs.
Solution Approach 2:
The patent changes the monitoring parameter (ranging rate) based on detected conditions. The system transitions between different monitoring states (high frequency, low frequency, suspended) based on the classifier's determination of motion versus stationary state, optimizing the balance between accuracy and power consumption.
2Use of energy by moving object
If location monitoring is suspended to save power, then power consumption is reduced, but location accuracy and response time deteriorate
Solution Approach 1:
The system performs preliminary classification of the device state using motion sensors and wireless signal analysis before deciding to suspend or continue monitoring. By predicting the device's motion state in advance, the system can proactively adjust monitoring frequency, ensuring accuracy is maintained when needed while saving power when appropriate.
Solution Approach 2:
The system uses feedback from motion classifiers and wireless signal strength indicators to continuously adjust monitoring frequency. The feedback loop ensures that monitoring is suspended only when the device is confirmed stationary, and resumed when motion is detected, maintaining accuracy while optimizing power consumption.
3Measurement precision
If geofence boundaries are set precisely, then location classification accuracy is improved, but false positive detections increase
Solution Approach 1:
The system dynamically adjusts geofence boundaries based on uncertainty measurements. When location uncertainty is high, the effective geofence boundary is expanded to prevent false exits. When uncertainty is low, the boundary is maintained at its precise definition. This dynamic adjustment resolves the contradiction between precision and false positives.
Solution Approach 2:
The patent changes the geofence boundary parameter based on measured location uncertainty. The system transitions between using the nominal boundary and an expanded boundary depending on the confidence level of location data, optimizing the balance between classification accuracy and false positive reduction.
4Loss of time
If update frequency for location data is increased, then latency is reduced, but power consumption increases
Solution Approach 1:
The system dynamically adjusts the update frequency of location data based on the device's proximity to the geofence and motion state. When the device is approaching the geofence boundary, update frequency increases to reduce latency. When the device is far from boundaries or stationary, update frequency decreases to save power. This dynamic adjustment resolves the time-energy tradeoff.
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
Improves location-based services by reducing power consumption, enhancing accuracy, and minimizing latency, ensuring correct geo-fence entries and exits.
Implementation Method 1
providing an unlock message to the lock mechanism, the message indicating a range between the lock mechanism and the mobile device is less than a threshold
Data Source
AI summary
Embodiments of the disclosed technology relate to improvements in location estimation and prediction for mobile devices while preserving energy. The use of classifiers is provided which preserves energy usage of the mobile device while providing contextually aware information for various stages. The use of a motion classifier and ranging in the context of access devices, the use of directional motion classifiers to reduce the latency in detection that a mobile device has entered a geofence area, and methods of improving location estimates and increasing geofence boundaries to prevent false exits from a geofenced area are disclosed.