CTU Chain of Custody via Visual Entity Identification
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Solution Overview
Problem
In environments with a large concentration of cargo transportation units (CTUs), it is challenging to determine the entities associated with individual CTUs, such as owners, operators, or those with access, which is crucial for tracking custody and managing efficiency, especially in unstructured settings like shipping yards or border crossings.
Innovation Solution
A server system equipped with a chain of custody determination engine that uses cameras and sensors on CTUs to capture images and identify entities through facial recognition and text processing, storing this information in a data repository to track ownership and access, enabling efficient management and notification of CTU locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking methods are used for CTUs, then operational simplicity is maintained, but tracking accuracy and entity identification capability deteriorate in environments with large concentrations of CTUs
Solution Approach 1:
The patent replaces manual tracking mechanisms with an automated image processing system. Cameras capture images of CTUs, and computer vision algorithms automatically identify and track entities associated with CTUs, substituting human visual inspection and manual recording with mechanical-optical-electronic systems that provide higher precision in environments with many CTUs.
Solution Approach 2:
The system creates visual copies of CTUs through image capture. By taking photographs or video frames of CTUs and their associated entities, the system creates reproducible visual records that can be analyzed, stored, and used for tracking without requiring direct physical interaction with each CTU, enabling efficient handling of large numbers of units.
2Productivity
If automated image processing is implemented for chain of custody tracking, then entity identification capability improves, but system complexity and computational requirements worsen
Solution Approach 1:
The system performs preliminary actions by capturing and preprocessing images of CTUs and their associated entities in advance. Image processing, entity identification, and chain of custody information generation are performed proactively as CTUs move through the supply chain, rather than reacting when information is needed, thereby improving overall tracking efficiency despite the computational complexity involved.
Data Source
Figure 1A
Figure 1B
Figure 2~3
AI summary
In some examples, a system receives an image captured by a camera of a first cargo transportation unit (CTU) in response to an activation of the camera, the activation of the camera of the first CTU responsive to an event. The system determines based on the image an identifier of an entity that owns, operates, or has access to the first CTU or a second CTU, and logs the identifier of the entity in chain of custody information stored in a storage medium.