Mobile Device Correlation for Shared-Vehicle Telematics
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Solution Overview
Problem
Existing telematics systems on mobile devices face challenges in efficiently correlating multiple devices within a common vehicle or trip, leading to unnecessary data collection, battery drain, and resource wastage, without effectively identifying the primary operator or passenger roles.
Innovation Solution
A method and system that determines correlated mobile devices within a common vehicle by broadcasting signals among devices, designating a leader device for data collection, and adjusting data collection based on device priority, battery status, and sensor type, thereby reducing redundant data collection and conserving resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all mobile devices in a vehicle continuously collect telematics data, then complete trip data is obtained, but battery consumption and network bandwidth usage increase significantly
Solution Approach 1:
The system segments the data collection responsibility among multiple devices by designating one device as the primary collector and others as secondary. The primary device collects comprehensive telematics data, while secondary devices collect only essential data or none at all, thereby reducing overall battery consumption while maintaining trip data completeness through coordinated data sharing.
Solution Approach 2:
The system merges the data collection efforts of multiple devices into a coordinated approach where the primary device's comprehensive data collection is supplemented by selective data from secondary devices. This merging allows the system to achieve complete trip data without requiring all devices to continuously collect data independently, thus reducing redundant battery consumption.
2Reliability
If all mobile devices in a vehicle continuously collect telematics data, then complete trip data is obtained, but network bandwidth usage and data redundancy increase
Solution Approach 1:
The system segments the data transmission burden by having the primary device transmit comprehensive telematics data to the server, while secondary devices transmit only essential data or trip confirmation signals. This segmentation significantly reduces network bandwidth usage while maintaining complete trip data availability through the primary device's transmissions.
Solution Approach 2:
Instead of requiring all devices to independently collect and transmit identical comprehensive data, the system uses the primary device as the main data source and has secondary devices selectively copy or supplement specific data elements when necessary. This copying approach eliminates redundant data transmission while ensuring trip data completeness.
3Reliability
If multiple mobile devices collect telematics data simultaneously, then data redundancy is reduced, but difficulty in identifying primary operator and passenger roles increases
Solution Approach 1:
The system introduces asymmetry in the roles of multiple devices by designating one device as the primary operator's device with full data collection privileges, while other devices are designated as passenger devices with limited or no data collection. This asymmetric role assignment simplifies the identification process and eliminates the complexity of determining device roles, as the primary device is clearly identified through its comprehensive data collection function.
4Reliability
If all mobile devices maintain active sensor collection, then real-time monitoring capability is maximized, but device complexity and processing overhead increase
Solution Approach 1:
The system segments the real-time monitoring function by assigning primary monitoring responsibilities to the primary device, which processes comprehensive telematics data in real-time. Secondary devices either perform minimal monitoring or rely on the primary device's processing, thereby reducing overall data processing overhead while maintaining real-time monitoring capability through the primary device's active processing.
Data Source
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AI summary
A method for identifying correlated mobile computing devices associated with a common vehicle or trip includes determining, based on data received from one or more first sensors associated with a first mobile computing device, that the first mobile computing device is on a trip in a vehicle, broadcasting, by the first mobile computing device, a signal indicating that the first mobile computing device is on the trip in the vehicle, receiving, by at least one second mobile computing device, the signal being broadcasted from the first mobile computing device, determining that the second mobile computing device is in the same vehicle as the first mobile computing device, and in response to the determination, causing the second mobile computing device to cease collection of data from one or more second sensors associated with the second mobile computing device.