Always-On Barometer Positioning for Low-Power Floor Detection
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Solution Overview
Problem
Utilizing pressure sensor readings in mobile devices is power-intensive due to the need for continuous sampling, which can lead to energy inefficiencies and reduced battery life, especially in applications requiring frequent altitude changes.
Innovation Solution
A dual-core processor design where one core handles application execution and another, low-power core continuously samples pressure data, allowing for efficient energy use by separating the power-intensive tasks from pressure monitoring, enabling floor disambiguation and other applications without significant energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous pressure sampling is performed by the application processor to enable floor detection applications, then positioning accuracy is improved, but power consumption increases significantly
Solution Approach 1:
The system segments the processing tasks by separating pressure sampling from application execution. A dedicated low-power sensor core continuously samples pressure data from the barometer, while the application processor only activates to process the sampled data when floor change detection is needed. This segmentation allows continuous monitoring without keeping the high-power application processor running constantly.
Solution Approach 2:
The sensor core acts as an intermediary between the barometer and the application processor. It continuously monitors pressure changes, detects when thresholds are exceeded, and only then triggers the application processor to perform floor disambiguation. This intermediary role eliminates the need for continuous application processor involvement, significantly reducing power consumption while maintaining accurate floor detection.
2Speed
If the application processor continuously monitors pressure data to detect floor changes, then response time is improved, but energy efficiency deteriorates
Solution Approach 1:
Instead of continuous monitoring by the application processor, the system uses periodic sampling by the low-power sensor core. The sensor core checks pressure data at regular intervals, and only activates the application processor when a pressure change exceeding the threshold is detected. This periodic action maintains fast response to floor changes while avoiding the energy waste of continuous high-power processing.
Solution Approach 2:
The sensor core performs self-service by autonomously monitoring pressure data, detecting threshold crossings, and triggering application processor activation only when necessary. This self-service capability eliminates the need for the application processor to continuously poll or monitor pressure data, maintaining rapid detection response while minimizing energy consumption through selective activation.
3Measurement precision
If pressure sampling rate is increased to improve floor detection accuracy, then measurement precision is improved, but power consumption increases
Solution Approach 1:
The system segments the sampling function from the processing function. The low-power sensor core handles high-rate pressure sampling continuously, while the high-power application processor only processes samples when floor changes are detected. This segmentation enables high sampling rates for accurate floor detection without proportionally increasing overall power consumption, as the expensive application processor remains dormant most of the time.
Solution Approach 2:
The system changes the operational parameters of different processors based on task requirements. The sensor core operates continuously at low power for sampling, while the application processor activates at high power only when needed for processing. This parameter change approach allows high sampling rates to be maintained without proportionally increasing total energy consumption, as each component operates at appropriate power levels for its specific function.
Data Source
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AI summary
Methods, apparatuses, and non-transitory processor-readable media of the present disclosure are presented for efficiently executing applications based on pressure sensor data. In some embodiments, a method includes monitoring pressure, and determining a rate of change in the pressure over time exceeds a predetermined rate-of-pressure-change threshold. The method further includes subsequently determining that the rate of change in the pressure over time no longer exceeds the predetermined rate-of-pressure-change threshold. The method further includes determining a change in pressure has exceeded a predetermined pressure-change threshold, and performing floor disambiguation.