Multi-Angle Vehicle Inspection Arrays for Accurate Defect Detection
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Solution Overview
Problem
Buyers of vehicles often lack accurate and efficient methods to inspect vehicles, especially in online sales environments, as in-person inspections are not feasible, leading to reliance on potentially inaccurate vehicle condition reports.
Innovation Solution
A vehicle inspection system comprising multiple sensor arrays and a computer hardware processor that captures and processes images of a vehicle's exterior and undercarriage, using machine learning to identify defects and generate condition reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensor arrays and machine learning processing are used to improve inspection accuracy, then measurement precision and reliability improve, but device complexity increases
Solution Approach 1:
The inspection system is divided into multiple specialized sensor arrays (exterior inspection system with first/second/third sensor arrays, undercarriage inspection system with fourth sensor array), each targeting specific vehicle regions. This segmentation allows each array to be optimized for its specific function while collectively achieving comprehensive high-precision inspection coverage.
Solution Approach 2:
The computer hardware processor performs multiple functions: capturing images from all sensor arrays, processing images through machine learning models, identifying defects, and generating condition reports. This multi-functionality consolidates complex operations into a single universal processing unit, managing system complexity while maintaining high inspection accuracy.
2Loss of information
If comprehensive vehicle inspection is performed to improve reliability of condition reports, then information completeness improves, but inspection time increases
Solution Approach 1:
The system captures all necessary images from multiple sensor arrays simultaneously or in rapid sequence before processing. The computer hardware processor is pre-configured with machine learning models ready to process the captured images immediately, eliminating delays between data collection and analysis, thus maintaining information completeness while minimizing inspection time.
Solution Approach 2:
Manual inspection processes are replaced with automated machine learning-based image processing. The computer hardware processor automatically analyzes images from all sensor arrays, identifies defects, and generates condition reports without human intervention, dramatically reducing inspection time while maintaining or improving information completeness through consistent automated evaluation.
Data Source
AI summary
Systems and techniques for inspecting vehicles. Some embodiments provide a system for vehicle inspection, including a support member having a first portion and a second portion angled relative to the first, and a plurality of sensor arrays coupled thereto. The plurality of sensor arrays may include respective sets of cameras oriented in multiple directions. The plurality of sensor arrays may be coupled to the support member at different positions. The plurality of sensor arrays may include: a first sensor array having one or more wheels of a vehicle in its field of view (FOV) when imaging the vehicle, a second sensor array having vehicle side in its FOV when imaging the vehicle, and a third sensor having a vehicle roof in its FOV when imaging the vehicle. The system may also include a processor configured to control the plurality of sensor arrays to capture images of the vehicle.