Cargo Tracking with Wireless Tags and Vision Positioning
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Solution Overview
Problem
Existing cargo identification and monitoring systems are inaccurate and time-consuming, leading to misidentification and improper loading, which can result in delays and safety issues during transportation.
Innovation Solution
A cargo tracking system combining a wireless system with identification tags and locators, and a vision system with electro-optical sensors to accurately identify and track cargo position, using trilateration and computer vision techniques for precise positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual inspection by operators is used to identify cargo, then human judgment can be applied, but identification accuracy decreases and time consumption increases
Solution Approach 1:
The patent replaces the mechanical visual inspection process with an automated vision system using electro-optical sensors (cameras) and image processing algorithms. The system captures images of cargo, automatically identifies cargo identifiers through computer vision, and retrieves cargo details from a database, eliminating manual visual inspection and significantly improving both accuracy and speed.
Solution Approach 2:
The system enables self-service identification where the cargo itself provides identification information through visible markers or labels that the vision system automatically detects and processes. The cargo's own visual features serve as the identification key, eliminating the need for external manual intervention.
2Measurement precision
If manual cargo identification is used, then system complexity is reduced, but cargo positioning accuracy deteriorates
Solution Approach 1:
The patent merges multiple functions into an integrated monitoring system: the vision system captures images, image processing algorithms identify cargo and determine position, and the database stores and retrieves cargo information. This combination of electro-optical sensing, computer vision, and database management creates a unified system that achieves high positioning accuracy while managing complexity through functional integration.
Solution Approach 2:
The vision system performs multiple functions simultaneously: it identifies cargo types, determines cargo position, and tracks cargo movement. The electro-optical sensors serve both identification and positioning purposes, reducing the need for separate specialized systems and managing overall system complexity.
3Reliability
If operators manually input cargo identification, then system cost is reduced, but identification accuracy and reliability decrease
Solution Approach 1:
The patent replaces manual data entry with automated optical recognition. The vision system captures images of cargo identifiers, computer vision algorithms automatically extract identification information, and the system queries the database for cargo details. This automation eliminates human error in data entry and significantly improves identification reliability.
Solution Approach 2:
The system incorporates feedback mechanisms where the vision system continuously monitors cargo, compares detected identifiers with database records, and verifies position information. This closed-loop verification process ensures high reliability by cross-checking information and detecting discrepancies automatically.
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
Enables accurate and efficient cargo identification and positioning with precision of less than 2m, reducing errors and enhancing loading efficiency by minimizing operator intervention.
Implementation Method 1
a wireless system with a plurality of locators configured to receive signals from tags
Implementation Method 2
a vision system with a plurality of electro-optical sensors configured to capture images of the cargo
Implementation Method 3
using trilateration and computer vision techniques for precise positioning
Data Source
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AI summary
Systems and method of tracking cargo. The tracking system includes a wireless system with tags configured to be connected to the cargo and to emit identification data, and locators configured to be connected to the vehicle and receive the identification data emitted from the tags. A vision system includes cameras positioned in the vehicle and configured to capture images of the cargo. A control unit includes processing circuitry configured to identify the cargo and track a position of the cargo based on signals transmitted from the tags and received by the locators and track the position of the cargo based on the images captured by the vision system.