Mobile Driving Session Detection With Adaptive Sensor Sampling
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Solution Overview
Problem
Existing systems struggle to accurately and efficiently monitor vehicle motion using mobile devices while minimizing battery consumption and computational effort.
Innovation Solution
A method for monitoring vehicle motion using a mobile device that collects activity data, determines user activity states, and collects motion data based on these states, allowing for efficient data collection and analysis, including the use of non-generic location and motion sensors to detect driving sessions and transmit relevant communications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous motion data collection is performed to accurately monitor vehicle motion, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system performs motion data collection at periodic intervals rather than continuously. The processor collects motion data from sensors at defined time points during the monitoring period, enabling accurate detection of driving sessions while significantly reducing battery consumption compared to continuous collection.
Solution Approach 2:
The system dynamically adjusts its monitoring behavior based on detected states. When a driving session is detected, the system activates more frequent or intensive data collection; when no driving is detected, it reduces to periodic sampling or standby mode, optimizing energy usage while maintaining detection accuracy.
2Measurement precision
If comprehensive activity data is collected to accurately determine user activity states, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments the monitoring process into distinct phases: periodic motion data collection, activity state determination based on collected data, and selective continuation of monitoring. This segmentation allows the system to process data in manageable chunks rather than continuously analyzing all possible parameters, reducing computational complexity while maintaining accuracy.
Solution Approach 2:
The system collects and processes only the necessary portion of activity data required to determine user activity states. Rather than continuously analyzing all sensor inputs, it selectively processes motion data at periodic intervals and only when relevant to driving detection, reducing computational effort while maintaining sufficient accuracy.
3Productivity
If motion data collection parameters are continuously adjusted to optimize monitoring, then productivity is improved, but use of energy increases
Solution Approach 1:
The system adjusts motion data collection parameters periodically rather than continuously. Collection parameters are updated at defined intervals based on accumulated data and detected patterns, enabling the system to optimize monitoring efficiency while avoiding the continuous parameter adjustments that would increase power consumption.
Data Source
AI summary
A method for monitoring vehicle motion using a mobile device associated with a user including collecting activity data at a mobile device associated with the user; determining a user activity state based on the activity data; determining motion data collection parameters associated with an operating state of the mobile device, based on the user activity state; and collecting motion data at the mobile device based on the motion data collection parameters.