Vehicle Identification via Dashboard Instrumentation Layout Analysis
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Solution Overview
Problem
Current systems lack an efficient method for identifying vehicle models based on images of their dashboards, which is essential for facilitating accurate vehicle identification and providing relevant information such as maintenance procedures and replaceable parts in network-based systems.
Innovation Solution
A vehicle identification machine is configured to receive images of vehicle dashboards, process the layout of instrumentation, and correlate this information with a data record to identify the vehicle model, providing notifications that include maintenance recommendations and part replacements based on the model and year of the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual vehicle identification methods are used, then accuracy can be maintained, but time consumption and effort increase significantly
Solution Approach 1:
The patent replaces manual visual inspection and mechanical identification processes with an automated image processing system. The system captures dashboard images and uses computer vision algorithms to automatically identify vehicle models, replacing the need for manual examination while maintaining or improving identification accuracy.
Solution Approach 2:
The system enables self-service vehicle identification where the vehicle itself (through its dashboard image) provides the identification information. The image processing system automatically extracts vehicle model data from the dashboard image without requiring human intervention, allowing the vehicle to 'identify itself' through its visual characteristics.
2Loss of information
If detailed vehicle information is collected manually, then completeness is improved, but resource consumption increases
Solution Approach 1:
The system extracts only the essential identification features from dashboard images, such as instrument cluster layout, gauge positions, and distinctive design elements. By selectively extracting only the necessary visual features rather than processing entire images or collecting all possible vehicle data, the system achieves complete vehicle identification with minimal computing resource consumption.
3Measurement precision
If traditional vehicle listing processes are used, then accuracy is maintained, but productivity decreases
Solution Approach 1:
The system performs preliminary vehicle identification by processing dashboard images before the actual vehicle listing process. By pre-identifying vehicle models through image analysis, the system prepares accurate vehicle information in advance, enabling faster listing while maintaining identification accuracy through automated model recognition.
Data Source
AI summary
A machine may be configured as a vehicle identification machine to identify a model of a vehicle based on an image that depicts a dashboard of the vehicle. As configured, the machine may receive an image of the dashboard, where the image depicts a layout of instrumentation within the dashboard. The machine may identify the layout of instrumentation by processing the image. For example, the machine may process the image by determining a position of an instrument within the layout of instrumentation, determining an outline of instrument, or both. The machine may access a data record that correlates a model of the vehicle with the identified layout of instrumentation and, based on the data record, identify the model of the vehicle. The machine may then provide a notification that references the vehicle, references the identified model of the vehicle, or references both.