Vehicle Data Processing via Driver-Worker Segmentation
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Solution Overview
Problem
Current technologies face challenges in efficiently processing and analyzing large amounts of measurement data from vehicles, particularly in real-time, due to increased complexity of control devices and limited bandwidth in communication networks, leading to high costs and inefficiencies in data transmission and analysis.
Innovation Solution
A method using a computer unit arrangement with multiple CPU-equipped units connected via a switch, where one unit acts as a driver to analyze and segment data into parallel-processable segments, optimizing storage and transmission by extracting structure and format information for dynamic transcoding and transmission over a global network, enabling efficient and rapid analysis of measurement data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If measurement data is stored in local memory of ECUs, then data can be captured at high sampling rates, but data volume cannot be transmitted in real-time due to limited communication bandwidth
Solution Approach 1:
The patent segments measurement data into different priority levels and categories (safety-relevant, comfort, diagnostic data). Only safety-critical data is transmitted in real-time, while other data is stored locally or transmitted asynchronously, resolving the contradiction between transmission speed and data volume.
Solution Approach 2:
The patent extracts and separates safety-relevant measurement data from the complete data set. By identifying and extracting only the critical subset of data for real-time transmission, the system achieves high-speed transmission without being constrained by the total data volume generated by all sensors.
2Productivity
If all measurement data is transmitted to cloud for analysis, then comprehensive analysis can be performed, but transmission costs and time delays increase significantly
Solution Approach 1:
The patent implements local quality by performing different processing levels at different locations: safety-critical data receives immediate local processing in ECUs, while other data undergoes batch processing. This resolves the contradiction by optimizing analysis efficiency for critical data without incurring transmission costs for all data.
Solution Approach 2:
The patent performs preliminary filtering, aggregation, and preprocessing of measurement data at the vehicle level before transmission. By conducting preliminary actions locally, the system reduces the volume of data requiring cloud transmission, thereby improving analysis efficiency while minimizing transmission time and costs.
3Quantity of substance
If data is pre-compressed and aggregated in local memory, then transmission bandwidth is reduced, but real-time processing capability is lost
Solution Approach 1:
The patent implements dynamic data handling where compression and aggregation levels adapt based on real-time requirements. For safety-critical data, minimal processing occurs to maintain real-time speed, while non-critical data undergoes aggressive compression. This dynamic approach resolves the contradiction between transmitted volume and processing speed.
4Measurement precision
If high sampling rates are used for all sensors, then measurement precision is improved, but data volume increases beyond manageable transmission capacity
Solution Approach 1:
The patent dynamically changes sampling parameters based on operational conditions and data priority. Critical sensors maintain high sampling rates for precision, while non-critical sensors use lower rates. This parameter adaptation resolves the contradiction between measurement precision and data volume by optimizing the sampling rate for each data source according to its importance.
Data Source
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AI summary
The invention relates to a method and to a system for processing measurement data, which in particular are generated during the operation of vehicles, by means of a computer unit assembly, wherein: at least a number of two computer units is provided and the computer units are connected with respect to data by means of at least one switch ("switch"); one of the computer units performs a control function as a driver ("driver") and the at least one other computer unit operates as a working unit ("worker"); the measurement data are provided to the computer unit assembly by means of a data stream and the measurement data have different data formats; the driver analyzes the measurement data with respect to the different data formats thereof and thereby extracts structure information and/or format information about the measurement data ("jump scan"); the driver creates a processing plan for the measurement data, in particular in the form of a table, from the structure information and/or format information; the processing plan is optimized with respect to the different data formats; the measurement data are divided into segments in accordance with the processing plan and are assigned to the working units for parallel processing, in particular for decoding, compression, storage, analysis and resynthesis.