Vehicle Observation Data Filtering for Redundant Cloud Transmission
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Solution Overview
Problem
Modern vehicles often transmit redundant, uninteresting, and inefficient observation data to remote devices, leading to increased communication costs and energy expenditure.
Innovation Solution
Implementing an in-vehicle selective information gathering system that aggregates and processes observation data from multiple vehicles before transmission to a cloud server, and a cloud-based system that identifies and flags vehicles sending redundant or inefficient data to cease transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If vehicles transmit all observation data to remote devices, then data availability is improved, but communication costs and energy expenditure increase
Solution Approach 1:
The system performs preliminary data aggregation and filtering at the vehicle level before transmission to remote devices. Observation data from multiple sensors is collected and processed locally, and only relevant data is transmitted, reducing unnecessary energy expenditure while maintaining data availability for analysis.
Solution Approach 2:
The system extracts and transmits only the most relevant observation data to remote devices after local processing. By identifying and separating essential information from redundant data, the system reduces communication energy costs while preserving critical data for further analysis.
2Loss of information
If vehicles transmit all observation data to remote devices, then data availability is improved, but financial costs increase
Solution Approach 1:
The system extracts and transmits only the most relevant observation data to remote devices after local processing. By identifying and separating essential information from redundant data, the system reduces communication volume and associated financial costs while preserving critical data for further analysis.
Solution Approach 2:
The system performs preliminary data aggregation and filtering at the vehicle level before transmission to remote devices. Observation data from multiple sensors is collected and processed locally, and only relevant data is transmitted, reducing unnecessary communication costs while maintaining data availability for analysis.
3Quantity of substance
If redundant data is transmitted to remote devices, then data redundancy is reduced, but data processing complexity increases
Solution Approach 1:
The system performs preliminary data aggregation and filtering at the vehicle level before transmission to remote devices. Observation data from multiple sensors is collected and processed locally, and only relevant data is transmitted, reducing unnecessary communication costs while maintaining data availability for analysis.
Solution Approach 2:
The system segments the data processing task between vehicles and remote devices. Local processing is performed at each vehicle to aggregate and filter observation data, while remote devices handle higher-level analysis. This segmentation reduces the processing burden on any single system while maintaining overall efficiency.
Data Source
AI summary
Systems and methods are provided for the reduction or elimination of redundant, uninteresting, and/or inefficient communications to remote devices (e.g. cloud servers) from vehicles collecting observation data. In-vehicle examples of the systems and methods are provided, wherein the associated methods for reducing or eliminating such redundant, uninteresting, and/or inefficient communications are performed on a vehicle. Cloud-based examples of the systems and methods are provided, wherein the associated methods for reducing or eliminating such redundant, uninteresting, and/or inefficient communications are performed on a remote device (e.g. a cloud server).