Movement Data Fusion for Driver-Passenger Role Detection
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Solution Overview
Problem
Existing technologies face challenges in accurately determining whether movement data from a user's mobile device corresponds to the user being a driver or a non-driver passenger in a vehicle, which is crucial for evaluating driving behaviors and generating personalized outputs.
Innovation Solution
The system evaluates movement data captured by a mobile device by combining sensor data such as GPS, accelerometer, and gyroscope data with additional data like application usage, public transportation schedules, and image data to determine the user's role in the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If pre-programmed responses are used in multi-computer systems, then system automation is improved, but adaptability to unexpected events deteriorates
Solution Approach 1:
The patent implements dynamic response selection where the system transitions from static pre-programmed responses to dynamic responses based on real-time movement data. The response action is selected dynamically according to the detected movement characteristics (speed, direction, acceleration) allowing the system to adapt to unexpected events while maintaining automation.
Solution Approach 2:
The system changes the parameter of response selection from fixed pre-programmed actions to parameter-based dynamic selection. By monitoring movement parameters (velocity, acceleration, direction) and selecting responses based on these real-time parameters, the system achieves both automation and adaptability to varying conditions.
2Reliability
If multiple computers are coordinated through centralized control, then system reliability is improved, but device complexity increases
Solution Approach 1:
The patent introduces movement data as an intermediary element that enables coordination between multiple computers without requiring complex centralized control. The movement detection unit and response selection unit act as intermediaries that process movement information and generate appropriate responses, simplifying the overall system architecture while maintaining reliability.
Solution Approach 2:
The system implements self-service coordination where each computer autonomously processes movement data and selects appropriate responses independently. This distributed self-service approach eliminates the need for complex centralized control while maintaining system reliability through coordinated autonomous actions.
3Adaptability or versatility
If response actions are selected based on movement data, then adaptability is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple possible response actions and their associated criteria. The system pre-processes movement data categories and prepares response selections in advance, allowing rapid response when movement events occur without requiring complex real-time processing, thus reducing processing time while maintaining adaptability.
Data Source
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AI summary
Methods, computer-readable media, systems, and/or apparatuses for evaluating movement data to identify a user as a driver or non-driver passenger are provided. In some examples, movement data may be received from a mobile device of a user. The movement data may include sensor data including location data, such as global positioning system (GPS) data, accelerometer and/or gyroscope data, and the like. Additional data may be retrieved from one or more other sources. For instance, additional data such as usage of applications on the mobile device, public transportation schedules and routes, image data, vehicle operation data, and the like, may be received and analyzed with the movement data to determine whether the user of the mobile device was a driver or non-driver passenger of the vehicle. Based on the determination, the data may be deleted in some examples or may be further processed to generate one or more outputs.