Mobile Device Location Tracking Using Motion Sensor Thresholds
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Solution Overview
Problem
Mobile devices face processing delays and battery inefficiencies when determining location using navigation sensors indoors or without GNSS, leading to poor user experience and inefficient battery use, especially in augmented reality applications.
Innovation Solution
Implementing motion sensors to determine when location updates are necessary, using ranging techniques efficiently and preloading AR applications based on device trajectory and historical usage patterns to conserve energy and reduce latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If navigation sensors are continuously used to determine device position, then location accuracy is improved, but processing time increases and battery energy is consumed
Solution Approach 1:
The system performs preliminary actions by using motion sensors to predict device movement and proactively determining when location updates are needed, rather than continuously updating location. This allows the system to prepare for location determination only when necessary, reducing unnecessary sensor activation and energy consumption while maintaining accurate location tracking when the device is actually moving.
2Measurement precision
If ranging sessions are performed frequently to update location, then location accuracy is improved, but processing delays occur
Solution Approach 1:
The system uses motion sensors to perform preliminary detection of device movement and predicts when location updates will be needed. By determining the need for ranging sessions in advance based on motion detection, the system avoids continuous ranging operations and reduces processing delays while maintaining location accuracy when updates are actually required.
3Use of energy by moving object
If motion sensors are used to detect device movement, then battery energy is conserved, but location determination may be delayed
Solution Approach 1:
The system performs preliminary detection using low-power motion sensors to identify when device movement occurs. This early detection allows the system to trigger ranging sessions only when necessary, conserving battery energy by avoiding continuous high-power sensor operation while ensuring location updates occur promptly when movement is detected.
Solution Approach 2:
The system dynamically adjusts its location determination strategy based on real-time motion sensor data. When motion is detected, the system transitions to active location determination; when no motion is detected, it enters a lower-power state. This dynamic adaptation optimizes the balance between energy consumption and location update timeliness based on actual device conditions.
Data Source
AI summary
In some implementations, responsive to a trigger signal at an associated first time, a mobile device generating a first location value using a first ranging session with one or more other devices. The technique may include storing the first location value in a memory. The technique may include tracking, using a motion sensor of the mobile device, motion of the mobile device to determine a present location relative to the first location value. Further, the technique may include determining that a present location for the mobile device has changed by a predetermined threshold amount from the first location value since the associated first time. Responsive to the present location for the mobile device having changed by more than the predetermined threshold amount since the associated first time, the technique may include, generating a second location value using a second ranging session with the one or more other devices.