Dynamic Vehicle Data Sampling Rate Adjustment
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Solution Overview
Problem
Vehicles with limited wireless bandwidth face challenges in transmitting sufficient data for remote diagnostics, as high sampling rates consume excessive bandwidth while low rates provide insufficient data for accurate feature analysis.
Innovation Solution
A server system that dynamically adjusts the sampling rate of vehicle data transmission based on variance analysis, increasing the rate when variance exceeds a threshold and decreasing it when variance is low, to optimize data collection and reduce unnecessary bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high sampling rate is used for vehicle data transmission, then data sufficiency for accurate feature analysis is improved, but wireless bandwidth consumption increases excessively
Solution Approach 1:
The patent implements dynamic sampling rate adjustment where the sampling rate is not fixed but changes over time based on computed variance metrics. The system transitions from a static sampling approach to a dynamic one where the sampling rate adapts to the actual data characteristics, resolving the contradiction between data sufficiency and bandwidth consumption.
Solution Approach 2:
The system changes the sampling rate parameter based on computed variance of vehicle data. By monitoring the variance metric and adjusting the sampling rate parameter accordingly (increasing when variance exceeds threshold, decreasing when it falls below threshold), the system optimizes the balance between data quality and bandwidth usage.
Solution Approach 3:
The patent implements a feedback mechanism where the server computes variance from received vehicle data, compares it against thresholds, and sends updated sampling rate queries back to the vehicles. This closed-loop feedback system allows the sampling rate to be continuously optimized based on actual data characteristics, resolving the contradiction between accurate feature analysis and bandwidth efficiency.
2Loss of energy
If low sampling rate is used for vehicle data transmission, then wireless bandwidth consumption is reduced, but data sufficiency for accurate feature analysis becomes insufficient
Solution Approach 1:
The feedback mechanism monitors variance in vehicle data and triggers sampling rate increases when variance exceeds the upper threshold, ensuring that data sufficiency is maintained when needed. This prevents premature reduction of sampling rate that would compromise feature analysis accuracy.
Solution Approach 2:
The sampling rate parameter is dynamically adjusted based on variance computation. When variance falls below the lower threshold, the system safely reduces the sampling rate to conserve bandwidth. This parameter change strategy ensures bandwidth efficiency is achieved only when data quality requirements are still met.
3Measurement precision
If increased sampling rate is applied continuously, then data quality for feature analysis is maintained, but unnecessary bandwidth usage increases
Solution Approach 1:
The system transitions from continuous high sampling rate to dynamic sampling rate adjustment. The sampling rate is high only when variance indicates it is needed for data quality, and low when variance permits bandwidth reduction. This dynamic behavior eliminates unnecessary bandwidth consumption while maintaining data quality when required.
Solution Approach 2:
Instead of applying high sampling rate continuously (excessive action), the system applies it partially only when variance exceeds thresholds indicating data quality concerns. This partial action approach maintains data quality when needed while avoiding unnecessary bandwidth usage during periods when lower sampling rates suffice.
Data Source
AI summary
A server includes an interface configured to communicate with a plurality of vehicles; and a processor, programmed to, send a query to the plurality of vehicles, the query identifying types of vehicle data and indicating an initial sampling rate, responsive to receiving the vehicle data sampled by the vehicles, process the vehicle data to obtain a feature result including an estimated value and a variance extending from the estimated value, and responsive to the variance being greater than a first threshold, send a first updated query indicating an increased sampling rate to the plurality of vehicles.