Mobile Context Determination Using Pressure and Inertial Sensors
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Solution Overview
Problem
Current mobile device contexts lack specificity, making it difficult to accurately determine the position of a mobile device, especially in environments like buildings where traditional positioning signals are unreliable, and fail to provide the precise information needed for operations such as pressure sensor calibration and emergency response.
Innovation Solution
More specific contexts are determined using a combination of data from pressure sensors, inertial sensors, and map data, including building-specific and travel-specific contexts, which refine the possible positions of a mobile device by analyzing vertical movements and pressure changes, allowing for more accurate positioning and sensor calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If general context determination methods are used, then the system is simple and energy-efficient, but the position determination accuracy is insufficient
Solution Approach 1:
The context determination is divided into multiple hierarchical levels: general context (e.g., moving vehicle, walking) and specific context (e.g., elevator, escalator, moving walkway). Each level uses different sensor combinations and analysis methods, allowing the system to achieve high precision when needed while maintaining simplicity for general cases.
Solution Approach 2:
The system dynamically adjusts the level of context specificity based on requirements. For emergency response applications requiring high precision, the system determines specific contexts using multiple sensors. For general applications, only general context is determined, optimizing resource usage while maintaining accuracy when necessary.
2Measurement precision
If multiple sensors and data sources are combined for specific context determination, then position accuracy improves, but energy consumption increases
Solution Approach 1:
The system applies partial action by using only the necessary subset of sensors and data sources for each specific context determination task. For example, pressure sensor data is used selectively when vertical movement contexts are suspected, rather than continuously activating all sensors. This reduces energy consumption while maintaining the ability to achieve high precision when specific contexts are determined.
3Loss of information
If general context information is used, then the system operates efficiently, but it cannot provide the specificity needed for emergency response and sensor calibration
Solution Approach 1:
The system changes the parameter of context specificity based on operational requirements. By analyzing sensor data patterns (pressure changes, vertical acceleration, orientation), the system determines whether a specific context exists. When specific contexts like elevators or escalators are detected, detailed context information is provided for emergency response and calibration operations, while maintaining efficient general operation for other scenarios.
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 significantly reduces the uncertainty in determining a mobile device's position, enhancing emergency response times and improving the calibration of pressure sensors by providing more precise context information.
Implementation Method 1
Different types of information can be collected by a mobile device for use in determining a context of that mobile device. Pressure information collected by a pressure sensor is unreliable... whether an altitude of a mobile device can be computed using measurements of pressure from a pressure sensor of the mobile device
Implementation Method 2
vector movement indicative of particular direction and amount of movement can be estimated using inertial sensor measurements from an accelerometer or other inertial sensor
Data Source
AI summary
Determining contexts of mobile devices. Particular embodiments described herein include machines that determine two estimated positions of a mobile device that respectively correspond to first and second locations at first and second times, acquire sets of terrain or structural information for first and second areas that respectively include the first and second estimated positions, use the acquired sets of information and the estimated positions to determine if the mobile device was near or within a structure at the first and second times, determine one or more values that are indicative of vertical movement by the mobile device during a period of time between the first time and the second time, compare the one or more values to one or more threshold conditions, and determine a context of the mobile device based on the comparison.