Sorting Support AI for Condition-Specific Prohibited-Article Detection
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Solution Overview
Problem
The increasing workload of inspection staff in customs and logistics due to the clever concealment of prohibited and restricted articles requires more efficient sorting and detection methods.
Innovation Solution
A sorting support apparatus and system utilizing AI-based learning models optimized for specific conditions, such as location, time, and sender, to determine the presence of prohibited articles in inspection targets, reducing the need for manual inspection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple learning models are stored for different usage conditions, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The inspection system is segmented into multiple specialized learning models, each optimized for specific usage conditions (e.g., different inspection targets, electromagnetic wave types, or operational environments). This segmentation allows the system to achieve high detection accuracy for each specific condition while managing overall complexity through modular organization of models.
Solution Approach 2:
The system dynamically selects and switches between different learning models based on the current usage condition. This dynamic adaptation allows the system to maintain high detection accuracy across varying conditions without requiring all models to be active simultaneously, thereby managing device complexity through selective activation.
2Measurement precision
If learning models are optimized for specific usage conditions, then detection accuracy is improved, but adaptability decreases
Solution Approach 1:
The system achieves universality by incorporating multiple specialized learning models that can be selected based on different usage conditions. Each model is optimized for its specific condition, yet the overall system remains universal and adaptable by switching between models to handle various inspection scenarios, prohibited articles, and electromagnetic wave types.
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
The system significantly reduces staff workload by improving detection accuracy and minimizing misjudgments through targeted learning models, enhancing the efficiency of logistics processes.
Implementation Method 1
X-ray scanning apparatuses are used in these inspections
Implementation Method 2
detecting a suspicious concealed object (25) through inspection by electromagnetic radiation in a range of 200 MHz-1 THz
Data Source
AI summary
A sorting support apparatus is provided with: an input part that inputs a transmission image obtained by radiating an inspection target with electromagnetic waves; a storage part that stores a plurality of learning models optimized respectively for at least one article and being associated with an assumed usage condition; and a determination part that selects one of the learning models based on a specified usage condition and uses the learning model to determine whether or not the one or more articles is contained in the inspection target.