Vehicle Data Collection System Selective Filtering
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Solution Overview
Problem
The integration of computing devices in vehicles generates vast amounts of data, leading to storage challenges and complexity in isolating relevant information, as existing systems indiscriminately collect all data without regard to relevance, consuming resources and complicating data retrieval.
Innovation Solution
A vehicle-based collection system that receives instructions from a remote server to selectively collect data by configuring internal filters to gather only event data matching defined parameters, discarding extraneous information and communicating the relevant data back to the requesting entity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all data is collected indiscriminately from vehicle systems, then complete information is available for analysis, but storage requirements increase and data retrieval becomes computationally intensive
Solution Approach 1:
The system performs preliminary filtering of data at the source before transmission or storage. Filters are configured to selectively pass only relevant data based on predefined criteria, preventing unnecessary data from entering the storage system in the first place. This resolves the contradiction by ensuring complete information about relevant events is captured while avoiding storage of irrelevant data.
Solution Approach 2:
Different filtering criteria are applied to different data sources and event types within the vehicle system. Each sensor and system can have customized filters tailored to its specific relevance, allowing the system to maintain high data quality for critical parameters while reducing overall data volume by excluding irrelevant information from less critical sources.
2Loss of information
If all data is collected indiscriminately from vehicle systems, then complete information is available for analysis, but data retrieval becomes computationally intensive
Solution Approach 1:
Data filtering is performed preliminarily at the data source before transmission or storage, rather than requiring comprehensive processing of all collected data later. This preliminary sorting of relevant from irrelevant data significantly reduces the computational burden during retrieval and analysis phases while preserving all necessary information.
Solution Approach 2:
The system extracts and isolates only the relevant data elements needed for specific analysis purposes from the broader vehicle data stream. By taking out only the necessary information at the filtering stage, the system avoids the computational complexity of searching through and processing large volumes of extraneous data during retrieval.
3Quantity of substance
If selective filtering is implemented to reduce data collection, then storage needs are reduced, but risk of filtering out relevant data increases
Solution Approach 1:
Filtering criteria and rules are established preliminarily based on thorough analysis of data requirements and relevance. This upfront configuration ensures that filters are designed to preserve all potentially relevant data while excluding only clearly unnecessary information, maintaining reliability while achieving data reduction.
Solution Approach 2:
The filtering system incorporates feedback mechanisms where filter performance is continuously monitored and evaluated. This allows for adjustment and refinement of filtering criteria to ensure that relevant data is not inadvertently excluded, maintaining data accuracy and reliability while achieving the goal of reduced data volume.
Data Source
AI summary
System, methods, and other embodiments described herein relate to controlling a vehicle to selectively collect event data. In one embodiment, a method includes, in response to receiving a collection request from a remote server, identifying defined parameters from the collection request about which data is to be harvested from the vehicle. The defined parameters include at least a content parameter that indicates criteria for determining which data associated with the vehicle is to be collected. The method includes collecting, from one or more vehicle systems of the vehicle, event data as a function of the content parameter and discarding extraneous data that does not match the content parameter. The method includes providing the event data to fulfill the collection request.