Layered Vehicle Cloud Control for Real-Time Data Processing
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Solution Overview
Problem
Conventional cloud technologies for vehicles inefficiently store and analyze data, leading to resource waste and inability to keep pace with rapid technological advancements, as they simply collect and store data without effective real-time processing or layer-based management.
Innovation Solution
A system utilizing a multilayered cloud structure for vehicles, where a first layer collects real-time data, a second layer processes and stores it with a delay, and a third layer performs advanced data processing and analysis, enabling efficient data management and real-time vehicle operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is collected and stored for a predetermined period (2-3 years) for vehicle performance improvement, then data availability for analysis is improved, but resource waste (storage space) increases and response speed decreases
Solution Approach 1:
The patent segments the cloud server into multiple layers (edge cloud layer, regional cloud layer, national cloud layer) with different data retention and processing functions. Each layer stores and processes data according to its specific needs, avoiding centralized storage of all historical data and reducing overall storage resource waste while maintaining data availability where needed.
Solution Approach 2:
The patent implements preliminary data processing and filtering at the edge cloud layer before data is transmitted to higher layers. This preliminary action reduces the volume of data that needs to be stored and processed centrally, decreasing storage resource requirements while ensuring that only relevant data is retained for long-term analysis.
2Loss of information
If data is stored for long-term analysis (2-3 years), then data completeness is improved, but technological development pace cannot be kept up and response time decreases
Solution Approach 1:
The patent divides data processing across multiple cloud layers with different time horizons and processing speeds. The edge cloud handles real-time data for immediate vehicle operation, while higher layers perform periodic analysis. This segmentation enables simultaneous real-time response and long-term analysis without compromising either speed or completeness.
Solution Approach 2:
The system performs preliminary data filtering, aggregation, and preprocessing at the edge cloud layer before transmitting to regional and national clouds. This preliminary action reduces the time required for subsequent analysis at higher layers, enabling faster technological development responses while maintaining data completeness through systematic preprocessing.
3Loss of information
If a single centralized cloud server stores all vehicle data, then data centralization is improved, but system complexity and processing efficiency decrease
Solution Approach 1:
The patent segments the centralized cloud server into a hierarchical multi-layer structure (edge cloud, regional cloud, national cloud). Each layer manages specific data types and processing tasks independently, reducing overall system complexity while maintaining data centralization through coordinated layers. This segmentation allows parallel processing and distributed management.
Solution Approach 2:
The patent transitions from a single-dimensional centralized server to a multi-dimensional hierarchical cloud architecture. Data is organized and processed across multiple dimensions (layers, regions, functions), enabling efficient management and processing while reducing complexity through distributed organization. This dimensional change allows simultaneous data centralization and processing efficiency.
4Speed
If real-time data processing is implemented for vehicle operation, then response speed is improved, but data processing resources and system complexity increase
Solution Approach 1:
The patent segments real-time data processing functions to the edge cloud layer, which is positioned close to vehicles and equipped with necessary processing capabilities. This segmentation enables real-time processing without requiring the entire cloud system to handle all real-time operations, reducing overall system complexity while maintaining fast response speeds for critical vehicle operations.
Data Source
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AI summary
A system for controlling vehicles using distributed cloud computing is provided. The system includes a first layer cloud server for collecting vehicle status data generated in a vehicle from the vehicle in real time and processing the collected data in real time. A second layer cloud server receives the vehicle status data generated in the vehicle, data collected by the first layer cloud server or data processed in the first layer cloud server, processes the received data, stores the processed data, and provides the stored data to the vehicle directly or via the first layer cloud server.