Abstract: A network of apparatuses that characterizes items is presented. A self-updating apparatus includes a processing unit that has a memory storing parameters that are useful for characterizing different items, and a processing module configured to automatically select sources from which to receive data, modify the parameters based on the data that is received, and to select recipients of modified parameters. Selection of sources and recipients is based on comparison of parameters between the processing module and the sources, and between the processing module and the recipients, respectively. The processing unit may include an artificial intelligence program (e.g., a neural network such as a machine learning program). When used in a network, the processing units may “train” other processing units in the network such that the characterization accuracy and range of each processing unit improves over time.

Abstract: A method and system for efficiently screening for dangerous threatening items are presented. The system includes an object unit designed to hold the object and a test unit including equipment for subjecting the object to a combination of two or more tests. There are sensors located in the object unit, wherein each of the sensors reads data resulting from testing the object and generates an output signal. A computation unit receives the output signal from each of the sensors and processes the output signals in parallel to determine a risk factor based on parameters resulting from the two or more tests. The parallel acquisition and processing of the output signals enhances accuracy. By testing a “batch” of objects at once, the system improves throughput.