Dense object detection system and method
AssigneeThe Johns Hopkins University
InventorsCarl V. Nelson, Mary R. Keller
Life of this patent
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Abstract
Provided herein is a method and system for detecting hidden dense objects in cargo containers including at least a cargo container platform with two-dimensional sensor arrays in juxtaposition therewith. The system further includes a process that estimates a weight and mass distribution data from a cargo manifest for the cargo container and available historical information about the cargo container. The historical weight and mass distribution is compared to the actual weight and mass distribution measured by the sensor arrays to detect discrepancies which will identify the tested cargo container as suspect and in need for further investigation.
Claims21
A system for detecting hidden dense objects in a plurality of cargo containers, the system comprising:
- (a) at least one cargo container platform capable of holding at least one cargo container;
- (b) at least one sensor array in juxtaposition with the at least one cargo container platform;
- and
- (c) a computing device for receiving actual information from the at least one sensor array, the actual information including the actual weight distribution and mass distribution of each cargo container of the plurality of cargo containers, retrieving available historical information about the cargo container and its content, estimating information including a historical weight distribution and mass distribution of the cargo container, and comparing the actual and estimated information to detect dense object anomalies,
- wherein the presence of the dense object anomalies identifios the cargo container as subject to further testing.
A method for detecting hidden dense objects in a plurality of cargo containers, the method comprising steps of:
- positioning at least one cargo container on a cargo container platform, the cargo container platform having at least one sensor array in juxtaposition therewith for providing actual information including an actual weight distribution and mass distribution of the cargo container to a computing device;
- retrieving available historical information about the cargo container and its contents;
- estimating information including a historical weight distribution and mass distribution of the cargo container;
- and
- comparing the actual and estimated information to detect dense object anomalies, wherein the presence of the dense object anomalies identifies the cargo container as being subject to further testing.
Dependencies are inferred from the claim text.