Vehicle Cargo Image Comparison for Early Falling-Object Detection
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Solution Overview
Problem
There is a need for efficient methods and systems to detect objects that are likely to fall from vehicle cargo, as such incidents can cause accidents, injuries, and fatalities, and existing systems fail to provide timely alerts.
Innovation Solution
A system that compares images of cargo taken at different times by a vehicle's mobile device or connected vehicles to determine the movement of cargo by analyzing key points and shapes, using image processing and machine learning to alert the driver or control the vehicle to secure the cargo.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image processing and comparison methods are used to detect cargo movement, then early detection capability is improved, but system complexity increases
Solution Approach 1:
The system creates a digital copy (image) of the cargo and compares it with a reference image. By working with image data rather than directly monitoring physical cargo, the system achieves non-contact detection with reduced mechanical complexity while maintaining reliable early detection capability.
Solution Approach 2:
The patent replaces direct mechanical monitoring of cargo with an optical/electronic system using cameras and image processing algorithms. This substitution eliminates the need for complex mechanical sensors and contact-based detection mechanisms while improving detection reliability through computational analysis.
2Measurement precision
If multiple images are captured and compared to detect cargo movement, then detection accuracy is improved, but time consumption increases
Solution Approach 1:
The system captures a reference image of the cargo in its secured state before potential movement occurs. This preliminary action establishes a baseline for comparison, enabling rapid detection of subsequent changes without requiring continuous lengthy analysis, thus improving accuracy while controlling time consumption.
Solution Approach 2:
The patent extracts key features and critical regions from the cargo images for comparison, rather than analyzing entire images in detail. This extraction approach maintains high detection accuracy by focusing on movement-critical areas while significantly reducing processing time.
Data Source
AI summary
A method for detecting objects that are likely to fall from vehicle cargo includes obtaining first data of a cargo of a first vehicle captured at a first time and second data of the cargo captured by a second vehicle in an environment of the first vehicle at a second time after the first time, determining a first distance between two key points of the first data or a first shape constructed by key points of the first data and a second distance between two key points of the second data or a second shape constructed by key points of the second data, and detecting a movement of the cargo based on a comparison of the first distance and the second distance or a comparison of the first shape and the second shape.