Vehicle Image Data Management via Operational Indexing
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Solution Overview
Problem
Current vehicle imaging systems face challenges in efficiently managing and accessing image data, as they typically discard old data when no accidents occur, require time-intensive operator review, and lack correlation of data from multiple cameras, making it difficult to find specific segments of interest, and data is not readily accessible remotely.
Innovation Solution
A vehicle image data management system that includes a controller and analysis processors to receive search parameters, identify and present matching image data from remotely stored data associated with operational data, allowing for efficient retrieval and correlation of image data across multiple vehicle systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If image data is stored temporarily on a loop and old data is discarded when no accidents occur, then storage space is conserved and system simplicity is maintained, but image data may be lost that could represent other problems with the vehicle and/or track
Solution Approach 1:
The system performs preliminary indexing of image data using operational data (location, time, speed, operational status) before any retrieval operation. This allows the system to prepare and organize data in advance, enabling efficient later retrieval without needing to retain all raw data indefinitely, thus balancing storage constraints with information preservation
Solution Approach 2:
The system creates indexed copies of operational data associated with image data. Instead of storing and retrieving entire video files, the system stores compressed metadata copies that represent key characteristics of the image data, allowing efficient storage while preserving the ability to retrieve relevant information
2Measurement precision
If an operator reviews large portions of image data to find smaller sections of interest, then complete coverage is ensured, but the process becomes time intensive
Solution Approach 1:
The system extracts and separates key operational data (location, time, speed, operational status) from the complete image data set. This extraction creates an independent index that can be searched directly, allowing operators to retrieve specific segments of interest without reviewing entire video files, thus dramatically reducing review time while maintaining search accuracy
Solution Approach 2:
The system segments the image data into discrete, indexable units associated with specific operational parameters. Each segment is tagged with metadata that allows independent searching and retrieval, transforming a continuous large-scale review task into targeted segment-based queries
3Quantity of substance
If multiple vehicle systems include multiple cameras capturing image data, then comprehensive coverage is achieved, but data correlation across systems becomes difficult
Solution Approach 1:
The system implements a universal indexing framework that works across multiple vehicle systems and camera types. The same operational data parameters (location, time, speed, operational status) are used to index data from all sources, creating a standardized interface that simplifies cross-system correlation while maintaining comprehensive coverage
Solution Approach 2:
The system merges data from multiple vehicle systems by correlating their operational data through common parameters such as location, time, and operational status. This creates a unified indexed structure that integrates data from multiple sources without requiring complex individual system management
4Reliability
If image data is stored onboard the vehicle systems, then data security and immediate availability are maintained, but remote access is not possible until the vehicle ends a current trip
Solution Approach 1:
The system introduces an intermediary communication interface that enables remote access to onboard image data through indexed queries. The intermediary translates remote search requests into local data retrievals based on operational data matching, allowing operators to access data remotely without requiring the vehicle to be physically present or complete a trip
Data Source
AI summary
An image management system includes a controller and one or more analysis processors. The controller is configured to receive search parameters that specify at least one of operational data or a range of operational data of one or more vehicle systems. The one or more analysis processors are configured to search remotely stored image data based on the search parameters to identify matching image data. The remotely stored image data was obtained by one or more imaging systems disposed onboard the one or more vehicle systems, and are associated with the operational data of the one or more vehicle systems that was current when the remotely stored image data was acquired. The one or more analysis processors also are configured to obtain the matching image data having the operational data specified by the search parameters and to present the matching image data to an operator.