Vehicle Event Recorder Discretization Facility
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Solution Overview
Problem
Existing vehicle event recording systems are limited in their ability to process and analyze non-discrete data, such as video and audio information, which is essential for fully characterizing events like accidents, leading to incomplete event records and requiring human intervention for data manipulation and analysis.
Innovation Solution
A system that captures both discrete and non-discrete data from vehicle sensors and uses a discretization facility to interpret and convert non-discrete data into machine-processable form, combining it with original data to create complete event datasets, enabling automated analysis and actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If video and audio data are captured and stored in vehicle event recorders, then event record completeness is improved, but data processing complexity increases due to inability to automatically process non-discrete data
Solution Approach 1:
A discretization facility is introduced as an intermediary component between the video/audio capture system and the analysis system. This facility converts non-discrete video and audio data into discrete, machine-processable data structures, enabling automated analysis without requiring complex manual intervention while preserving complete event records
Solution Approach 2:
The patent replaces manual human analysis of video/audio data with an automated discretization and analysis system. The system uses algorithms to automatically interpret non-discrete data, substitute human operators in the data processing chain, and generate actionable insights through automated event characterization
2Measurement precision
If manual intervention is used for data manipulation and analysis, then analysis accuracy can be maintained, but productivity decreases due to time-consuming processes
Solution Approach 1:
The discretization facility enables the system to process and analyze its own captured data automatically without requiring external human intervention. The system self-services by converting its own non-discrete data into analyzable formats and performing event characterization autonomously, significantly improving productivity while maintaining accuracy through structured analysis protocols
3Extent of automation
If only discrete data is processed, then automated analysis is enabled, but information completeness is reduced by excluding non-discrete video and audio information
Solution Approach 1:
The patent transforms the state of non-discrete video and audio data by changing its parameters through discretization. The continuous data is converted into discrete parameters and structured formats that maintain the essential information content while becoming compatible with automated digital processing systems, thus preserving information completeness while enabling automation
Data Source
AI summary
Exception event recorders and analysis systems include: vehicle mounted sensors arranged as a vehicle event recorder to capture both discrete and non-discrete data; a discretization facility; a database; and an analysis server all coupled together as a computer network. Motor vehicles with video cameras and onboard diagnostic systems capture data when the vehicle is involved in a crash or other anomaly (an ‘event’). In station where interpretation of non-discrete data is rendered, i.e. a discretization facility, captured data is used as a basis for production of supplemental discrete data to further characterize the event. Such interpreted data is joined to captured data and inserted into a database in a structure which is searchable and which supports logical or mathematical analysis by automated machines. A coupled analysis server is arranged to test stored data for prescribed conditions and upon finding such, to initiate further actions appropriate for the detected condition.