Patent Description:
It is known to provide security screening at a variety of locations where people congregate. For example, passengers and their baggage are screened for prohibited items at airports. Also, people and their belongings are sometimes screened for prohibited items at concerts and sporting events. Speed is a factor in screening, as screening checkpoints can become bottlenecks.

Screening systems are known for example from <CIT>, which discloses screening of mail parcels, or <CIT> which discloses a multi stage baggage scanner.

A screening system according to an example of the present invention includes a plurality of detectors about a screening area. Each detector including a sensor is configured to detect information from one or more objects moving along a path from an entrance to an exit of the screening area. The plurality of detectors includes a first detector configured to detect information from a first location of the path, and a second detector configured to detect information from a second location of the path. The second detector is configured to adapt its functionality based on a finding of the first detector for a given one of the one or more objects. The first and second detectors are each configured to analyze chemical information from the objects, and the second detector utilizes a detection library and is configured to eliminate items from its detection library from consideration for the given one of the one or more objects based on the chemical information gathered by the first detector for the given one of the one or more objects.

Optionally, the detection library includes at least one of the following groups of restricted compounds: chemical warfare agents, biological warfare agents, toxic industrial chemicals, explosives, narcotics, and radiological materials.

Optionally, the chemical information gathered by the first detector is a fluorescent response of an analyte sampled from the given one of the one or more objects.

Optionally, to adapt its functionality, the second detector is configured to adapt one or more of the following: dwell time, illumination intenstity, wavelength, spot size, detection threshold, and library of target compounds.

Optionally, a controller includes a processor is configured to correlate data from the plurality of detectors for the given one of the one or more objects, and determine a security risk for the given one of the one or more objects based on the correlated data.

Optionally, the one or more objects are first objects, the screening area is a first screening area, and the screening system includes a third detector situated in a second screening area that is separate from the first screening area. The third detector is configured to detect information from one or more second objects associated with particular ones of the one or more first objects. The controller is configured to further base its determination of the security risk for the given one of the first objects on data from the third detector for a given one of the one or more second objects that is associated with the given one of the first objects.

Optionally, the controller is configured to change how the third detector analyzes a particular one of the second objects based on data from one or more of the detectors for a particular one of the first objects that is associated with the particular one of the second objects.

Optionally, the controller is configured to modify a dictionary or one or more weighting factors that the third detector uses to analyze the particular one of the second objects based on the data from one or more of the detectors for the particular one of the first objects that is associated with the particular one of the second objects.

Optionally, the controller is configured to change how one or more of the plurality of detectors analyze a particular one of the first objects based on data from the third detector for a particular one of the second objects that is associated with the particular one of the first objects.

Optionally, the controller is configured to modify a dictionary or one or more weighting factors that one of the detectors uses to analyze the particular one of the first objects based on the data from one or more of the detectors for the particular one of the second objects that is assocated with the particular one of the first objects.

Optionally, a conveyor is configured to move the one ore more second objects through the second screening area.

Optionally, an imaging device is configured to record images of objects moving along the path, and the controller is configured to correlate the images of individual ones of the first objects with the data from the plurality of detectors for those individual objects.

Optionally, the controller is configured to assign an electronic tag to images of a particular first object and to data related to the first object from one or more of the detectors as part of the correlation.

Optionally, the objects are humans, and the imaging device is a third detector configured to screen the humans for one or more biological or behavioral characteristics.

Optionally, the one or more bodily threat indications include one or more of body temperature above a predefined threshold, sweating, fidgeting, and human bulkiness.

Optionally, an automated transport device is configured to move the objects from the entrance to the exit of the screening area along the path.

Optionally, the automated transport device includes a moving walkway.

Optionally, the moving walkway includes a skirt guard, and at least one of the first and second detectors is disposed within the skirt guard. The skirt guard includes at least one aspirating inlet that provides fluid communication between the object and at least one of the plurality of detectors.

Optionally, one of the plurality of detectors is a metal detector.

Optionally, one of the plurality of detectors is a millimeter wave scanner.

A method of installing detectors about a screening area according to an example of the present invention includes installing a first detector and installing a second detector about a screening area. The first detector is configured to detect information from one or more objects at a first location on a path between an entrance and an exit of the screening area. The second detector is configured to detect information from the one or more objects at a second location on the path that is different from the first location. The method also includes adapting functionality of the second detector for a given one of the one or more objects based on a finding of the first detector for the given one of the one or more objects. The adapting includes eliminating compounds from a detection library of the second detector from consideration for the given one of the one or more objects based on the chemical information gathered by the first detector for the given one of the one or more objects.

Optionally, the path includes a moving walkway configured to move the objects towards the exit, and the first and second locations are locations along the moving walkway.

The embodiments, examples, and alternatives of the preceding paragraphs, the claims, or the following description and drawings, including any of their various aspects or respective individual features, may be taken independently or in any combination. Features described in connection with one embodiment are applicable to all embodiments, unless such features are incompatible.

As screening checkpoints can become bottlenecks in locations where people congregate, it is desirable to increase the throughput of people at checkpoints by improving the inflow and outflow from these locations, resulting in an improved experience for visitors. An exemplary system described herein is capable of achieving integration of movement and screening, and automating certain security functions. <FIG> illustrates an example screening system <NUM> that includes a plurality of detectors 14A-C for a screening area <NUM> that includes a moving walkway <NUM>. The detectors <NUM> are configured to detect information about people, animals, and/or objects (collectively "objects") moving along the moving walkway <NUM> within the screening area <NUM>. The collected "information" can include data for a chemical analysis or a physical analysis, for example.

The moving walkway <NUM> may include a handrail <NUM> and a skirt guard <NUM>. The skirt guard <NUM> may include a plurality of aspirating inlets <NUM> configured to suck air into the skirt guard <NUM> and provide for fluid communication between an object on the moving walkway <NUM> and a detector 14A that is housed within the skirt guard <NUM>. Although only one detector 14A is shown in the skirt guard <NUM>, it is understood that multiple detectors 14A could be housed within the skirt guard <NUM>. An additional detector 14B may straddle the moving walkway <NUM> so that an object can be scanned while being moved along the moving walkway <NUM>. Also, a detector 14C may be situated on a wall <NUM> that is proximate to the moving walkway <NUM>. Although detector 14C is shown situated on the wall <NUM>, detector 14C may be situated on the ceiling or other surface proximate to the moving walkway <NUM>. In one example, the detector 14A is a chemical sniffer, the detector 14B is a metal detector, and the detector 14C is an imaging device. Below, reference numerals <NUM>, <NUM>, <NUM>, and <NUM> are generically used without being limited to the example of <FIG>.

Note that although <FIG> depicts a moving walkway, a screening area <NUM> may include a hallway <NUM> with aspirating inlets <NUM> present in a skirting between a wall and the floor, in a wall, or in a floor or ceiling of the screening area <NUM>. Optionally, one or more detectors 14A may be housed within skirting <NUM> or within a wall, floor, or ceiling, for example near an aspirating inlet <NUM> which may appear to be an air vent; one or more detectors 14B may be housed within an arch or other structure straddling a hallway <NUM>; and one or more detectors 14C may be situated on a wall, ceiling, or other surface proximate to the hallway <NUM>. Thus, screening system <NUM> may be deployed in any relatively confined space such as, for example, a hallway, moving walkway, conveyor, escalator, or any similar space where people, animals, and/or objects are likely to transit.

<FIG> is a schematic view of an example screening system <NUM> that includes a controller <NUM> and a plurality of detectors <NUM>. One or more objects <NUM> move along a path <NUM> within screening area <NUM>, and the path <NUM> includes a plurality of locations 21A-N. In one example, the path <NUM> includes a moving walkway <NUM> (as shown in <FIG>). Detector 14A is configured to detect information from objects <NUM> at location 21A on the path <NUM>, detector 14B is configured to detect information from objects <NUM> at location 21B on the path <NUM>, and so on. The location 21B is subsequent to the location 21A on the path <NUM>, and so on. The path <NUM> extends from an entrance <NUM> to an exit <NUM> of the screening area <NUM>. In one example, the objects <NUM> are people, animals, and/or baggage and the screening area <NUM> is part of a location where people congregate such as an airport terminal, theater entrance, or stadium entrance.

The screening system <NUM> is utilized to detect threats in areas where it is desirable to screen for hazardous conditions and materials, such as buildings, facilities, factories, special events, work zones, transportation centers, government buildings, high value assets, activities, and objects. In a sequential screening system as shown in <FIG>, the screening occurs as the objects <NUM> move through the screening system <NUM>. The screening system <NUM> utilizes multiple detectors <NUM> to inspect people and belongings with each detector <NUM> utilizing the results of previous detectors <NUM> to modify their functionality to enhance detection performance. As used herein, "functionality" can refer to variable capabilities within the range of performance of the device, including but not limited to, for example: dwell time, illumination intensity, wavelength, spot size, detection thresholds, and library of targets interrogated. In some embodiments, a change in functionality may include disabling a capability in order to speed or intensify performance of a different capability. The functionality modification may include a change in a detection library or a change in a fitting function (such as equation <NUM> below), for example.

Each location <NUM> is within the detection area of its respective detector <NUM>. In one example, these detection areas are non-overlapping, such that each detector <NUM> has its own discrete detection area that is not shared with another detector <NUM>. In another example, the detection areas do overlap. In one such example, the detection areas of a pair of detectors <NUM> overlap when the first detector <NUM> of the pair can complete its detection function while still providing adequate time for the second detector <NUM> in the pair to modify its functionality based on the detection of the first detector <NUM>. In another example, one pair of detectors may have substantially similar functions but each have a different detection area, e.g. the front or back of an object moving along a path <NUM>, or a pair of detectors may be positioned on opposite walls <NUM> or a ceiling along a line substantially perpendicular to path <NUM> such that each detector <NUM> has an opposite or mirror-angled line of sight to objects side by side on walkway <NUM>, but the pair may nevertheless have detection areas that overlap.

At least one of the detectors <NUM> may be characterized as a situational awareness detector that provides information on the characteristics of the objects <NUM> that impact its measurements. In one such example in which the first detector 14A is a situational awareness detector, the detector 14A takes an initial evaluation of an object <NUM> to determine information about the object <NUM>, such as one or more of chemical composition, orientation, distance, perspective, reflectivity, and other environmental factors to be associated with the detection spectra. The data is then used to refine the functionality of subsequent detectors 14B - N (e.g., the data collected by those detectors) by modifying their functionality and/or respective detection algorithms. In this fashion, a composite spectrum is developed to predict a substrate/background in the region of interest. In order to enable this determination, a reduced order optical system model may be applied to the data associated with the object. Optical measurements can be affected by optical effects such as skew, interference, resonance and frequency shifting. By subtracting the composite spectrum from the measured spectrum, background substrate interactions (skew, interference, resonance and frequency shifting) can be eliminated.

At least one of the detectors <NUM> may be characterized as a prioritization detector which may include an imaging device (e.g., a camera or imaging device such as thermal imaging devices, radar, sonar, etc.) and is utilized to identify specific regions of interest for the objects <NUM> (e.g., handles of luggage or the hands of a people). The recognition problem of locating parts/attributes within a larger object or environment poses a challenge. Appearance changes due to factors such as changes in illumination, pose, or even clutter cause visual ambiguity (i.e., the same object looks different when viewed from different angles). In one example, a Convolutional Deep Neural Network (CDNN) may be used to address this challenge by localizing features of interest in camera imagery for subsequent detector <NUM> inspection.

The CDNN may require initial training and test datasets to discern areas of interest. In one example, the Caffe deep learning framework may be utilized to for training the CDNN on how to discriminate objects, such as hands and handles of luggage, which is useful in determining associations between people and luggage. As objects <NUM> move through the screening area <NUM>, perspective can change, so tracking moving objects <NUM> such as people and belongings in images, e.g., in surveillance video, may be achieved using Kalman and Particle filters.

At least one of the detectors <NUM> may be characterized as a non-contact sensor (or "standoff detector") that does not require contact with an object <NUM> to sense a characteristic of the object <NUM>. The standoff detector <NUM> inspects objects for threats and may utilize information from one or more situational awareness and/or prioritization detectors <NUM>. A standoff detector <NUM> typically uses non-contact methods to identify threats. Some example standoff detectors known in the art may include but are not limited to any of chemical sniffers, metal detectors, X-ray scanners, millimeter wave scanners, thermal scanners, UV detectors, optical scanners, laser induced breakdown spectroscopy scanners, and standoff photoacoustic spectroscopy scanners, for example.

All such detectors remotely scan within a detection area, and may be used alone or in combination to identify specific types of threats. For example, a chemical sniffer <NUM> may be configured to obtain information of chemicals present on or about an object <NUM>. A chemical sniffer <NUM> may include a detection library of groups of restricted chemicals compounds which are typically indicative of one or more of the following example threats or threat classes, such as: chemical warefare agents (CWA) (e.g., sarin, soman, and cyclosarin), biological warfare agents (BWA) (e.g., plague, smallpox, and anthrax), toxic industrial chemicals (e.g., phosgene, sulfuric acid, and nitric acid), explosives (e.g., dynamite), narcotics (e.g., methamphetamine, heroin, cocaine), and radiological materials (e.g., plutonium and uranium), and other chemicals and materials hazardous to humans, animals or property. A person of ordinary skill in the art would be familiar with particular detection devices configured to detect such threats or threat classes.

In another example, a metal detector <NUM> may be configured to detect metal on or in an object <NUM>. In a further example, an X-ray scanner <NUM> may obtain an X-ray image of an object (e.g., for detecting metal). In further examples: millimeter wave scanner <NUM> is configured to detect items concealed by or within an object <NUM>. A thermal scanner <NUM> is configured to detect a thermal profile of an object <NUM>, which may be useful for determining a physiological or biological characteristic of a person, such as body temperature. A UV detector <NUM> is configured to detect a fluorescent response of an object <NUM>, which can be an identifying chemical trait. An optical scanner <NUM> is configured to analyze images of an object <NUM> to determine behavioral characteristics (e.g., fidgeting, coughing, bulkiness, etc.). In one example, the optical scanner includes a shortwave infrared (SWIR) scanner and/or longwave infrared (LWIR) scanner. The foregoing are non-limiting examples, and other types of detectors <NUM> could be used.

As decribed above, the functionality of one or more exemplary detectors <NUM> may be modified to enhance detection performance of the detector <NUM>, of another detector <NUM>, or of the screening system <NUM> as a whole. At least one of the detectors <NUM> is configured to adapt its functionality for a given one of the objects <NUM> based on a finding of a preceding detector <NUM> in the screening area <NUM> for the given one of the objects <NUM>.

In one example, with respect to an exemplary chemical sniffer 14B with a detection library as decribed above, an exemplary functionality adaptation includes eliminating items from the detection library for consideration during the scanning and analysis of a given one of the objects <NUM> based on chemical information gathered by a preceding detector <NUM> for the object <NUM>. In one such example, detector 14A is a UV detector that determines a fluorescent response for an analyte sampled from a given one of the objects <NUM>, and detector 14B excludes items from its detection library that could not provide the detected fluorescent response. This could potentially narrow a library of thousands of compounds down to a library of under one hundred compounds, providing for speed and overall efficiency improvements in the screening system <NUM>.

Identifying the chemical components of an analyte is a challenge because there are hundreds or thousands of possible constituent chemicals. Given that any output for chemical identification of a threat should be sparse - a mixture of relatively few significant things - an algorithm within detector <NUM> and/or controller <NUM> may efficiently identify potential threats by, for example, using a mixed-norm, sparse optimization approach. A representative method utilizes an Akaike information criterion (AIC) for model order selection. That is, <MAT> where A is the matrix of known or measured chemical spectra (the library), y is the measured analyte, x is the desired sparse vector representing the concentration of each component from the library that is in the analyte, and µ is a weight factor between accuracy and model order as explained below. A processor <NUM> in detector <NUM> and/or controller <NUM> may be configured to execute the algorithm (see <FIG>, described below).

In order to speed detection, an optimization-based approach can be applied to solve equation <NUM>. As also explained above, modification of the library within a detector 14B may be based on the output of a previous detector 14A. In one example, the first detector 14A may be capable of scanning for threats that absorb IR light between <NUM>-<NUM>. Based on the result from detector 14A, controller <NUM> may modify the library of a second detector 14B capable of determining absorption of UV light (or the second detector 14B may modify its own library). For example, if during scanning and analysis of objects <NUM> first detector 14A determines the presence or absence of chemical agents hazardous to humans (for example, those known to be used in chemical warfare) which are detectable in the wavelength range of <NUM>-<NUM>, While scanning object <NUM> the second detector 14B may modify its functionality by eliminating entries in the library that are consistent or inconsistent with the hazardous chemical agents as determined by detector 14A. In the present example, the hazardous chemical agents can be eliminated if no absorption was recorded or, if absorption was recorded, the library would be refined to only the hazardous chemical agents.

In the above-described configuration, another parameter that may be tuned to adjust the functionality of a detector 14B is the choice of the factor µ which controls the tradeoff between sparsity (number of constituent chemicals) and accuracy (ability to match the measured spectrum). Rather than trying to select a single µ that is good for all conditions, µ can vary for a detector 14N based on the input from other detectors 14A - N-<NUM>. By way of explanation, in one exemplary scenario a previous detector 14A may optimize its results for µ. The optimization technique can be linear optimization, physical model or Bayesian optimization. The corrected weighting factor may be used by an algorithm performed by controller <NUM> in order to enable minimization of the modeled spectra and the results from the detector 14A. In one example the updated weighting factor is utilized in the AIC to minimize the Kullback-Leibler divergence between the model and the unknown true composition.

The controller <NUM> is configured to correlate data from the plurality of detectors 14A-N for individual ones of the objects <NUM>, and determine a security risk for individual ones of the objects <NUM> based on the correlated information. In one example, each detector <NUM> provides its own risk assessment, and the controller <NUM> provides a global risk assessment based on the combined discrete risk assessments of the individual detectors 14AN. In an example, the situational awareness detector 14A, the prioritization detector 14B, and at least one standoff detector 14C-N each provide a threat determination about an object <NUM> to the controller <NUM>. The controller <NUM> utilizes the output of the detectors 14C-N to assign a threat level to the object <NUM> to determine the risk. The assigned threat level is the output from fusing the output from the detectors 14A-N. In one example the fusing of data is accomplished using one of a central limit theorem, Kalman filter, Bayesian networks, Dempster-Shafer or a convolutional neural network.

<FIG> is a schematic view of an example hardware configuration for a detector <NUM> in which the detector <NUM> includes a processor <NUM>, memory <NUM>, one or more input/output ("I/O") devices <NUM>, and one or more sensors <NUM>. The processor <NUM> includes one or more microprocessors, microcontrollers, application specific integrated circuits (ASICs), or the like, for example.

The memory <NUM> includes any one or combination of volatile memory elements (e.g., random access memory (RAM, such as DRAM, SRAM, SDRAM, VRAM, etc.)) and/or nonvolatile memory elements (e.g., ROM, hard drive, tape, CD-ROM, etc.). The memory <NUM> can also have a distributed architecture, where various components are situated remotely from one another, but can be accessed by the processor <NUM>.

The memory <NUM> stores program instructions that configure the processor <NUM> to utilize the sensor(s) <NUM> to detect information about an object <NUM>. For some detectors, such as in the example of a chemical sniffer <NUM>, the memory <NUM> may also store data which may be used to identify hazardous conditions, such as a detection library of prohibited chemical compounds and their signatures.

The configuration of the sensor(s) <NUM> may vary depending on a type of the detector <NUM>. For example, in one example chemical sniffer <NUM>, the one or more sensors <NUM> may include a surface plasmon resonance (SPR) sensing element to detect information about an analyte sampled from an object <NUM>. In one example, the one or more sensors <NUM> may include an imaging sensor configured to obtain images of an object <NUM> as part of an X-ray scanner <NUM>, millimeter wave scanner <NUM>, or optical scanner <NUM>.

The one or more I/O devices <NUM> may be configured to communicate with the controller <NUM> and/or with other detectors <NUM>.

As shown in <FIG>, the controller <NUM> and/or <NUM> utilizes a similar architecture to what is shown in <FIG>, and similarly includes a processor <NUM>, memory <NUM>, and one or more I/O devices <NUM> that provides for communication between the controller <NUM> and detectors 14A-N.

<FIG> illustrates an example implementation of the screening system <NUM>. In this disclosure, like reference numerals designate like elements where appropriate and reference numerals with the addition of one-hundred or multiples thereof designate modified elements that are understood to incorporate the same features and benefits of the corresponding elements.

The screening system <NUM> includes a screening area <NUM> including a first screening area 120A for one or more first objects <NUM> (e.g., people), and a second screening area 120B for one or more second objects <NUM> associated with particular ones of the first objects (e.g. belongings of the people <NUM>), such as baggage <NUM> or personal items <NUM>. A moving walkway <NUM> in the first screening area 120A is configured to move the first objects <NUM> from an entrance <NUM> towards an exit <NUM> of the screening area <NUM>. A conveyor <NUM> in the second screening area 120B is configured to move the second objects <NUM> towards the exit <NUM> as well. In the example of <FIG>, the moving walkway <NUM> moves along longitudinal axis A1, and the conveyor <NUM> moves along longitudinal axis A2 that is generally perpendicular to longitudinal axis A1.

Detectors 114A-E may be situated along the moving walkway <NUM> for detecting information from the first objects <NUM> on the moving walkway <NUM>. Detectors 214A-D may be situated along the conveyor <NUM> for obtaining information from the second objects <NUM>.

The controller <NUM> is in communication with the detectors 114A-E and 214A-D and an imaging device <NUM>.

The imaging device <NUM> may be configured to record images of first objects <NUM> moving along moving walkway <NUM> and associated second objects <NUM> moving along conveyor <NUM>. The controller <NUM> may be configured to associate a second object <NUM> with a first object <NUM> based on images from the imaging device <NUM> (e.g., associate a person or people <NUM> with one or more suitcases or personal items <NUM>), and correspondingly correlate information from detectors <NUM> for a specific first object <NUM> with information from detectors <NUM> for that specific first object's associated second object(s) <NUM>. In one example, this includes performing facial recognition for a person <NUM> for identification purposes (e.g., maintaining a historical log of passenger scanning information).

The correlated information for a first object <NUM> is used to determine a security risk for a first object <NUM>. The controller <NUM> is configured to correlate information from the plurality of detectors <NUM> that are inspecting the first object <NUM>, and determine a security risk for the first object <NUM> based on the correlated data. In one example, the controller <NUM> assigns the detector output to the first object <NUM> via an electronic tag. The tag is a unique identification that enables information with the same tag to be correlated. The tagged data transmitted to the controller <NUM> is then compared to known thresholds to determine the security risk.

In one example, the controller <NUM> is configured to change how one or more of the detectors <NUM> analyze a first object <NUM> based on data from one or more of the detectors <NUM> for one or more second objects <NUM> associated with the first object <NUM>. For example, the controller <NUM> may change how one or more of the detectors <NUM> analyze a person <NUM> or people <NUM> based on data from one or more of the detectors <NUM> for one or more items of personal belongings <NUM> such as baggage. In one example, tracking of first object(s) <NUM> and second object(s) <NUM> can be achieved using one or more detectors <NUM> that includes a video camera or series of video cameras. Such detectors may include detectors <NUM> or detectors <NUM>, or separate detectors <NUM> deployed about the screening area (i.e., in or proximate to the screening area <NUM>). As described below, the association may be made between first object(s) <NUM> and second object(s) <NUM> via algorithms in the controller <NUM> before the first object(s) <NUM> and second objects <NUM> are separated in the screening system <NUM>.

For example, the tracking and association algorithm in controller <NUM> may include Kalman and Particle filters for tracking moving objects such as people <NUM> and/or personal belongings <NUM> in surveillance video. As detectors <NUM> inspect the second objects <NUM> they may output one, some, or all of a risk level, a potential threat, and/or threat class associated with each of the second objects <NUM>. This output is then sent to the controller <NUM>. In some embodiments the detectors <NUM> may provide raw or processed sensor data to the controller <NUM> which will evaluate one, some, or all of a risk level, a potential threat, and/or threat class associated with each of the second objects <NUM>. Subsequently the controller <NUM> may update the detectors <NUM> that are screening the first objects <NUM> to confirm or mitigate a determined security risk by modifying the functionality of detectors <NUM>, e.g. by modifying dictionaries or weighting factors of the detectors <NUM>. As used herein, a threat or threat class can include any of the following, for example: chemical warfare agents (CWA), biological warfare agents (BWA), toxic industrial chemicals, explosives, narcotics, radiological materials, and other chemicals and materials hazardous to humans, animals, or property.

In one example, the controller <NUM> may change how one or more of the detectors <NUM> analyze a second object <NUM> algorithmically associated with a first object <NUM> based on data from one or more of the detectors <NUM> for the first object <NUM>. For example, the controller <NUM> may change how one or more of the detectors <NUM> analyze one or more personal belongings <NUM>, such as baggage, based on data from one or more of the detectors <NUM> for a person <NUM> or group of people <NUM>.

For example, a video camera or series of video cameras may be used to track of first object(s) <NUM> and second objects <NUM>. As previously described, one or more tracking and association algorithms in controller <NUM>, which may include Kalman and Particle filters for tracking moving objects, may associate first object(s) <NUM> and second object(s) <NUM> before the first object(s) <NUM> and second objects <NUM> are separated in the screening system <NUM>. As detectors <NUM> inspect each first object <NUM> they may output one, some, or all of a risk level, a potential threat, and/or threat class associated with the first object <NUM>. In some embodiments the detectors <NUM> may provide raw or processed sensor data to the controller <NUM> which will evaluate one, some, or all of a risk level, a potential threat, and/or threat class associated with each of the first objects <NUM>. This output is then sent to the controller <NUM>. Subsequently the controller <NUM> may update the remaining detectors <NUM> that are screening the second object(s) <NUM> to confirm or mitigate the determined security risk by modifying the functionality of detectors <NUM>, e.g. by modifying dictionaries or weighting factors of the detectors <NUM>.

In one example, the imaging device <NUM> also functions as an optical detection device by analyzing image data to detect biological or behavior characteristics of a first object <NUM> such as a person (e.g., body temperature above a predefined threshold, sweatiness, fidgeting, bulkiness, etc.). These characteristics can be indicative of a person <NUM> intending to inflict harm. For example, an elevated body temperature above a predefined threshold, sweating, and/or fidgeting (e.g., more than a predefined amount of typical human movement) can be indicative of a high stress response of the person <NUM>. Also, bulkiness can be indicative that a person <NUM> may be concealing a prohibited object such as a weapon. In one particular example, the imaging device <NUM> is configured to detect an infrared signature of a person <NUM> to determine if the body temperature of that person is elevated above a predefined threshold.

In one example, the detectors 114A-B are chemical sniffers that include detection libraries, and chemical sniffer 114B has a detection library responsive to vary based on the readings of chemical sniffer 114A, e.g. chemical sniffer 114B may be configured to reduce its detection library or select a specific detection library based on the findings of chemical sniffer 114A. In one example, detector 114C is a metal detector (e.g., a pulse induction metal detector), detector 114D is another chemical sniffer 114D, and detector 114E is a millimeter wave scanner that is reserved for humans flagged as having a risk above a predefined threshold based on the output of scanners 114A-D and/or 214A-D.

In one example, detectors 214A and 214D are chemical sniffer detectors having detection libraries, at least one of <NUM> A and 214D having a variable detection library, and detectors 214B-C are X-ray detectors, where detector 214D similarly alters its functionality based on the findings of detector 214A.

<FIG> is a flowchart <NUM> of an example method of installing detectors about a screening area. A first detector 14A is installed about a screening area <NUM> (step <NUM>). The first detector 14A is positioned to detect information from objects <NUM> at a first location 21A on the path <NUM> between the entrance <NUM> and the exit <NUM> of the screening area <NUM>. A second detector 14B is installed about the screening area <NUM> (step <NUM>). The second detector 14B is positioned to detect information from objects <NUM> at a second location 21B on the path <NUM> that is subsequent to the first location 21A along the path <NUM> from the entrance <NUM> to the exit <NUM>. Functionality of the second detector 14B is adapted for a given one of the one or more objects <NUM> based on a finding of the first detector 14A for the given one of the objects (step <NUM>).

Instead of traditional checkpoints where a scanner becomes a bottleneck for large crowds, in the screening systems <NUM> described herein, objects are scanned as they move without significant delay throughout a screening area <NUM> (e.g., either moving down a hallway or on an automated transport device such as a conveyor belt or moving walkway). By performing scanning while objects <NUM> are moving, the time during which an object <NUM> is screened is increased without causing bottlenecks associated with stationary scanning.

Prior art checkpoint screening processes are slow, which can cause excessive wait times and occupy a large amount of floor space in transportation facilities for queuing items to be scanned. The systems described herein increase the throughput of people at a checkpoint by integrating object movement and detectors. This provides reduced wait times and an improved travel experience, and also provides increased automation of checkpoint security functions.

Claim 1:
A screening system (<NUM>) comprising:
a plurality of detectors (14A-C) about a screening area (<NUM>), each detector comprising a sensor configured to detect information from one or more objects (<NUM>) moving along a path (<NUM>) from an entrance(<NUM>) to an exit (<NUM>) of the screening area, the plurality of detectors comprising a first detector (14A) configured to detect information from a first location (21A) of the path, and a second detector (14B) configured to detect information from a second location (21B) of the path; wherein the second detector is configured to adapt its functionality based on a finding of the first detector for a given one of the one or more objects;
characterized by:
the first and second detectors are each configured to analyze chemical information from the objects, and the second detector utilizes a detection library and is configured to eliminate one or more compounds from the detection library for the given one of the one or more objects based on the chemical information gathered by the first detector for the given one of the one or more objects.