Cargo Load Detection Using Light Dot Array Distortion
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Solution Overview
Problem
Current cargo load detection methods in containers or trailers are inefficient due to reliance on manual yard checks or sensors that face challenges from load surface conditions, temperature, and field-of-view limitations, making it difficult to accurately determine the loading status of containers.
Innovation Solution
A computing device equipped with a light array and camera is used to project light dots onto the container surface, capturing images to detect distortions caused by cargo loads, allowing for accurate calculation of load position and size through image processing, and optionally utilizing edge detection to determine load presence and volume.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual yard checks are used to determine trailer loading status, then human resources and time are consumed, but the method provides direct observation of loading status
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated optical measurement system. A camera captures images of the trailer interior, and image processing algorithms automatically determine loading status by analyzing the position of trailers walls and floors relative to the camera, eliminating the need for manual yard checks while maintaining detection accuracy.
2Extent of automation
If ultrasonic or light sensors with TOF technology are used for automatic load detection, then automation is achieved, but load surface conditions, temperature, and field-of-view create measurement problems
Solution Approach 1:
The patent substitutes ultrasonic or light sensors with a camera-based imaging system. Instead of using time-of-flight measurements that are sensitive to surface conditions and temperature, the system captures images and processes them to determine the positions of trailers walls and floors, providing automated detection that is robust to environmental variations.
Solution Approach 2:
The patent creates a visual copy (image) of the trailer interior and processes this copy to extract loading information. The camera captures the physical space, and image processing algorithms analyze the captured image to determine the positions of structural elements and calculate loading status, replacing direct physical measurement with optical copying and digital analysis.
3Productivity
If camera-based techniques with light arrays are used for cargo load detection, then manual intervention is reduced, but the system requires image processing to analyze light distortions
Solution Approach 1:
The patent uses a camera to capture images of the trailer interior and employs image processing algorithms to automatically analyze the images and determine loading status. This substitution of manual inspection with automated optical measurement and digital image analysis increases productivity while the complexity is managed through software-based processing of captured images.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method provides a more efficient and accurate means of determining cargo load status, reducing manual intervention and overcoming sensor limitations by using camera-based techniques to analyze light array distortions and edge interruptions, thereby improving the accuracy and speed of load detection.
Implementation Method 1
projecting at least one light dot within an array of light dots towards a surface of the container; capturing an image of the at least one light dot on the surface of the container
Data Source
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AI summary
A method for cargo load detection in a container by a computing device, the method including projecting at least one light dot within an array of light dots towards a surface of the container; capturing an image of the at least one light dot on the surface of the container; and using the captured image to determine cargo loading within the container.