Real-Time Cargo Size Estimation Using Camera Imaging
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Solution Overview
Problem
Existing parcel tracking systems for delivery companies do not provide detailed information necessary for predicting parcel loading, route planning, and resource allocation, limiting their efficiency in managing cargo spaces and vehicle routes.
Innovation Solution
A cargo tracking system utilizing cameras and central electronic computing devices to estimate cargo size in real-time, compute remaining cargo space, and transmit data for detailed information management, including volume, location, and direction of travel, using algorithms and computer vision technology.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional tagging and identification systems are used to track parcels, then parcel identification is achieved, but detailed information for predictions and optimization is insufficient
Solution Approach 1:
The patent replaces traditional mechanical tagging and identification systems with an optical imaging system using cameras. The camera captures images of cargo, and image processing algorithms automatically extract detailed information such as cargo size, shape, and characteristics. This substitution provides comprehensive cargo information without requiring complex manual tagging systems, thereby reducing information loss while maintaining acceptable system complexity.
Solution Approach 2:
The patent creates visual copies of cargo through camera imaging. Instead of relying on physical tags or labels, the system captures optical images of cargo and processes these images to extract meaningful data. This copying approach provides detailed cargo information (dimensions, shape, position) without adding physical complexity to the cargo itself, resolving the contradiction between information completeness and system complexity.
2Productivity
If real-time cargo tracking is implemented, then operational efficiency is improved, but data processing requirements increase
Solution Approach 1:
The patent extracts only the essential and relevant information from captured cargo images, such as cargo dimensions, position, and key characteristics. Rather than processing and storing all raw image data, the system selectively extracts meaningful parameters needed for operational decisions. This extraction approach enables real-time tracking and improves operational efficiency while keeping data processing requirements and data volume manageable.
3Volume of stationary object
If detailed cargo size estimation is performed, then cargo space optimization is improved, but measurement precision requirements increase
Solution Approach 1:
The patent introduces image processing algorithms as an intermediary between the camera and the cargo space optimization process. The algorithms process camera images to estimate cargo dimensions and calculate cargo volume. This intermediary approach provides sufficiently accurate measurements for space optimization without requiring extreme measurement precision, as the algorithms can work with approximate dimensional data to achieve effective cargo space utilization.
Data Source
AI summary
A cargo tracking system for tracking a cargo includes a camera and a central electronic computing device. The cargo, during a loading of the cargo into a cargo space for delivering the cargo, is trackable by the camera. An information about the cargo is transmittable by the camera to the central electronic computing device. The camera is configured to estimate a size of the cargo in real time and, depending on the estimated size of the cargo and depending on a predetermined cargo size of the cargo space, the camera is configured to compute a remaining cargo size of the cargo space and to transmit the computed remaining cargo size to the central electronic computing device in real time.