Sensor Hub Indoor-Outdoor Detection With Activity-Based Low Power Sensing
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Solution Overview
Problem
Existing methods for determining whether a mobile device is indoors or outdoors often rely on high-power GPS or satellite navigation, which is inefficient in terms of power consumption and user experience.
Innovation Solution
The use of accelerometer data to determine user activity, combined with additional sensor data from magnetometers, ambient light sensors, and gyroscopes, to accurately classify the environment as indoor or outdoor, thereby reducing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS or satellite navigation is used to determine indoor/outdoor environment, then detection accuracy is improved, but power consumption increases
Solution Approach 1:
The patent segments the detection task into multiple stages: first using low-power accelerometer data to determine user activity, then selectively engaging additional sensors (magnetometer, ambient light sensor, gyroscope) only when needed based on the activity classification. This segmentation avoids continuous high-power GPS usage while maintaining detection accuracy through coordinated multi-sensor operation only when necessary.
Solution Approach 2:
The patent introduces accelerometer-based user activity detection as an intermediary layer between the device and the final indoor/outdoor determination. This intermediary classification system filters when additional high-power sensors are needed, acting as a mediator that reduces overall power consumption by preventing unnecessary activation of magnetometers, ambient light sensors, and gyroscopes in situations where accelerometer data alone suffices.
2Measurement precision
If multiple sensors (magnetometer, ambient light sensor, gyroscope) are used for environment detection, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic sensor activation where the system adapts which sensors are active based on real-time accelerometer-based activity classification. Rather than continuously operating all sensors or using a fixed configuration, the system dynamically adjusts sensor usage according to the detected user activity state, optimizing the balance between detection accuracy and system complexity management.
Solution Approach 2:
The patent performs preliminary classification of user activity using only accelerometer data before activating additional sensors. This preliminary action filters out cases where simple activity recognition suffices for environment determination, preventing unnecessary complexity from continuously operating multiple sensors and reducing the computational burden of processing data from all sensors in every situation.
3Reliability
If continuous high-power detection methods are used, then detection reliability is improved, but battery life decreases
Solution Approach 1:
The patent implements periodic activation of high-power sensors based on detected user activity patterns rather than continuous operation. The system periodically engages magnetometers, ambient light sensors, and gyroscopes only when accelerometer-based activity classification indicates conditions warranting enhanced detection, thereby maintaining reliability through strategic periodic measurement while extending battery life by avoiding continuous high-power consumption.
Data Source
AI summary
Techniques for low power indoor/outdoor detection are disclosed. In the illustrative embodiment, an integrated sensor hub receives data from an accelerometer. The sensor hub processes the accelerometer data to determine an activity of the user. Depending on the activity of the user, the sensor hub may determine whether the compute device is indoors or outdoors or may receive data from additional sensors, such as a magnetometer, a gyroscope, or an ambient light sensor. The additional sensor data may be used to determine whether the compute device is inside or outside.