Device Mode Detection Using Weighted Sensor Fusion
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Solution Overview
Problem
Existing methods for device mode detection in electronic devices, such as smartphones, face challenges in balancing accuracy and power consumption, with GPS and WiFi-based approaches consuming significant power and accelerometer-based methods producing inconsistent results with false positives and negatives.
Innovation Solution
A method that involves scanning for initial movement indications with a low-power sensor, such as an accelerometer, and activating a set of secondary sensors like GPS, WiFi, and location sensors to validate the device mode, weighting their inputs to determine a device mode, thereby reducing power consumption and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS or WiFi scanning is used to determine location and device mode, then measurement precision is improved, but use of energy increases significantly
Solution Approach 1:
The patent segments the device mode detection process into multiple stages: initial detection using low-power accelerometer data, intermediate validation using WiFi scanning, and final confirmation using GPS. This segmentation allows the system to use high-precision sensors only when necessary, reducing overall power consumption while maintaining detection accuracy.
Solution Approach 2:
The system performs preliminary device mode detection using the accelerometer before activating more power-intensive GPS or WiFi scanning. This preliminary action filters out obvious non-vehicle cases early, preventing unnecessary activation of high-power sensors and reducing overall energy consumption.
2Use of energy by moving object
If accelerometer-based vehicle mode detection is used, then use of energy is reduced, but reliability deteriorates due to false positives and false negatives
Solution Approach 1:
The patent merges multiple detection methods (accelerometer, WiFi scanning, GPS) into a unified device mode detection system. The accelerometer provides continuous low-power monitoring while WiFi and GPS provide periodic validation, combining the advantages of low power consumption with high reliability to eliminate false positives and negatives.
Solution Approach 2:
The system implements feedback mechanisms where accelerometer data continuously monitors device motion patterns and triggers validation scans when vehicle-mode indicators are detected. This feedback loop allows the system to maintain high reliability by validating accelerometer-based detections with additional sensor data only when necessary.
3Use of energy by moving object
If accelerometer data is used for vehicle mode detection, then power consumption is reduced, but measurement precision deteriorates at stop lights and during brief stops
Solution Approach 1:
The system performs preliminary detection using accelerometer data to identify potential vehicle mode scenarios, then activates WiFi or GPS scanning as a follow-up validation step. This preliminary action approach ensures that stops at traffic lights or brief pauses are properly validated, maintaining measurement precision without continuous high-power sensor activation.
Solution Approach 2:
The patent implements periodic validation scanning using WiFi or GPS at intervals, rather than continuous monitoring. This periodic action maintains measurement precision by regularly checking device mode status while keeping power consumption low during intervals between scans.
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
This approach reduces power consumption while enhancing the accuracy of device mode detection, minimizing false positives and negatives, and ensuring that device features are activated at the correct times.
Implementation Method 1
A first sensor of the electronic device scans for a first movement indication
Data Source
AI summary
A method on an electronic device is described. A first sensor of the electronic device scans for a first movement indication. A set of second sensors of the electronic device are activated based on the first movement indication. The set of second sensors scan for a respective set of second movement indications. The set of second movement indications are weighted based on a respective set of sensor weight values to obtain a weighted set of second movement indications. The weighted set of second movement indications is combined to determine a device mode of the electronic device. The device mode is updated based on the combination of the weighted set.