Fleet Vehicle Data Collection for Bandwidth-Limited OTA Uploads
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Solution Overview
Problem
The existing methods for data collection and transmission from a fleet of vehicles to a host system face challenges due to high latency, uncertain data value, and limited bandwidth, especially in 5G networks, necessitating a more efficient and targeted approach for real-time or near-real-time data upload.
Innovation Solution
A method where vehicles select and transmit only high-value data snippets based on predefined metrics and policies, using reinforcement learning to optimize data selection and deletion, thereby reducing the amount of data transmitted over-the-air.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all recording data is transmitted over-the-air from vehicles to host system, then complete data is available for analysis, but transmission bandwidth is exceeded and latency increases
Solution Approach 1:
The patent segments the data transmission process by dividing recording data into individual data snippets, each evaluated independently for transmission value. This allows selective transmission of only high-value snippets rather than transmitting all data, thus reducing overall transmission volume while maintaining essential information quality.
Solution Approach 2:
The patent applies local quality by assigning different quality values to different data snippets based on their individual importance metrics. High-value snippets (those meeting transmission criteria) are transmitted, while low-value snippets are discarded, creating a non-uniform quality distribution across the data set that optimizes bandwidth utilization.
2Quantity of substance
If data transmission is reduced to optimize bandwidth usage, then transmission volume decreases, but data value and completeness may be compromised
Solution Approach 1:
The patent performs preliminary evaluation of data snippets before transmission by calculating their importance metrics and comparing them against transmission criteria. This preliminary action identifies which snippets are worth transmitting, ensuring that bandwidth is allocated to high-value data while preventing transmission of redundant information.
Solution Approach 2:
The patent implements a feedback mechanism where transmission decisions are based on evaluated metrics of data snippets. The system continuously assesses data quality and adjusts transmission selections accordingly, ensuring that the most valuable data is prioritized for transmission while maintaining overall data integrity.
3Loss of information
If data is collected and stored locally in vehicles, then data availability is maintained, but storage resources and power consumption increase
Solution Approach 1:
The patent extracts only the essential high-value data snippets from the complete recording data set for transmission to the host system. By removing redundant low-value data before transmission, the system reduces the amount of data that needs to be managed and processed, thereby reducing storage requirements and associated power consumption while maintaining data availability for critical analysis.
4Productivity
If selective data transmission is implemented, then transmission efficiency improves, but system complexity increases due to data evaluation requirements
Solution Approach 1:
The patent applies preliminary action by pre-defining transmission criteria and evaluation metrics before the data transmission process begins. This preparation work establishes clear rules for data selection, simplifying the actual transmission decision-making process and reducing runtime computational complexity while maintaining transmission efficiency.
Data Source
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AI summary
A method, carried out in a vehicle (100), includes: a) downloading over-the-air from a host system (200) a data collection target including a data value metric that is a function assigning a data value to a piece of data at a given point in time, representing an amount of progress towards an atomic collection target; b) collecting data from data sources (110) in the vehicle (100) over time while the vehicle (100) is driving; c) recording the collected data in a storing module (142); d) computing the data values of the recording data, according to the data value metric; e) selecting, from the recording data, recording data snippets of high value within a time window, based on the computed data values; f) uploading only the selected recording data snippets of high value to the host system (200) over-the-air.