Multi-Threat Detection System

[0001] The present invention relates generally to a system for detecting the presence of a hazardous object, and more specifically to a system for detecting the presence of a threatening object by means of multiple parallel tests.

BACKGROUND OF THE INVENTION [0002] At present, security systems used at the checkpoints of some public places, including airports and government buildings, are usually a certain combination of imaging, metal detector and chemical analysis. Chemical analysis is usually carried out using a table explosive trace detector (ETD), which tests for the presence of such materials, swabs or air samples taken from the object being inspected (e.g. from the bag). [0003] Unfortunately, the security control systems currently in use are not as reliable as they could be. For example, X-ray scans identify dangerous objects based on optical density, but many harmless objects have a density similar to that of security-threatening objects, with the natural consequence being a high percentage of false negative results. For X-ray or computed tomography imaging, the accuracy of the inspection depends largely on the vigilance and ability to assess the human-characterizing operator viewing the images during baggage scanning. Although many systems enable the automatic visual classification of suspicious objects, human alertness and judgment still play an important role. Due to distraction, fatigue and the natural limitation of the human attention span, a control system in which so much depends on human judgment cannot achieve the optimal level of accuracy. What's more, because imaging relies heavily on the visualization of the objects being checked, the passenger can mask or hide the harmful object that poses a threat, thus avoiding detection by imaging.

[0004] Attempts are being made to increase the accuracy of security systems operating at checkpoints by combining various techniques, usually imaging, metal detector and chemical analysis. Most often, such checks are carried out using three separate devices placed side by side. The objects are checked separately and sequentially using these devices: one test after another. For example, in the airport security system, X-ray imaging can be used and only baggage identified as suspicious can be chemically analyzed. Similarly, passengers can first be asked to pass through the gate for preliminary metal detection, and only when the control in such a gate triggers an alarm, subject them to a closer control by a metal detector, performed by an officer.

[0005] The problem with this type of serial m / sequential combination of checks is that the overall accuracy depends highly on the accuracy of each individual check, and in some cases on the accuracy of the first check. For example, if no chemical analysis is performed when the baggage passes X-rays successfully, its use is only helpful if the baggage has been correctly identified as a suspect by x-raying. If an operator

- looking at x-rays will not notice a potentially dangerous object, the easy availability of chemical analysis will not change the fact that such an object has passed through the security system. [0006] Although the use of several methods for checking each passenger and piece of luggage would be an obvious way to increase the accuracy of security checks, such a solution is impractical because it would result in passengers wasting excessive time to pass through the screening. The cost of such a system would also be prohibitively high. In practice, the accuracy of tests during security checks is balanced and controlled by the necessity of passengers passing through the system at a reasonable rate. In particular, if a test that gives a high percentage of false positives is used first, for example x-rays, passenger flow is slowed down because many pieces of luggage that do not contain hazardous items are subjected to a second test unnecessarily.

[0007] A system and method is therefore needed to allow passengers to pass the security checkpoint at a reasonable speed without compromising the accuracy of the check.

[0008] Document W02004023413 discloses: a sensor network that provides the ability to detect, classify and identify factors distributed over a large area, such as a geographical area or a building. High detection probability with a low probability of false alarm is ensured by processing information provided by a set of sensors.

[0009] Document WO09921148 discloses an integrated passage system for detecting hidden or suspicious objects with one or more of the devices, such as a dielectric scanning device, an X-ray scanning device, a metal detection device, a camera device for millimeter waves and a device for collecting and analyzing steam.

SUMMARY [0010] According to the invention, a device according to claim 1 is provided. [0011] The device may comprise a control module comprising equipment subjecting a combination object to two or more different types of tests, and modular object modules can be attached to the control module. Each of the object modules can be designed to hold the object, and the control module to examine objects in different object modules. The calculation module can receive output signals from each of the field modules and the control module and can then determine the risk factor for each object in the different field modules.

[0012] The invention makes it possible to identify an object in an object module in which more than one sensor is located and subject to a combination of tests to determine the properties of that object. Output signals from sensors in the object module can be read and individually processed to generate parameter values. The parameter values ​​are compiled to determine the risk factor that determines the probability of the presence of an object at risk in the facility.

BRIEF DESCRIPTION OF THE DRAWINGS [0013]

Fig. 1 is a block diagram showing the main components of a multi-threat detection system in accordance with the invention.

Fig. 2 is a block diagram of an example version of the multi-threat detection system.

-3Fig. 3 is a block diagram illustrating the components of the calculation module used to implement the method of identifying a dangerous item.

Fig. 4 shows an exemplary version of a multi-threat detection system comprising a single control module and more than one object module.

Fig. 5 is a block diagram showing the control module and object modules.

Fig. 6 shows another example version of a multi-threat detection system where the object is a human (or any animal).

Fig. 7 shows yet another example version of the multi-threat detection system for checking inanimate objects and people.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS [0014] Embodiments of the present invention are discussed herein in the context of the security system used at the checkpoint. It should be noted, however, that the embodiments shown in this document are merely exemplary implementations, and the scope of the invention is not limited to the applications or practical examples described in the document. For example, the system according to the invention may be useful, among others, for automated inspection of small packages and postal items and packaged consumer goods (e.g. food, medicine).

[0015] The use of the multi-threat detection system of the invention is to detect the presence of various threat objects. "Hazardous Object" means any substance or combination of substances and objects that may be of interest to security services, including, but not limited to, explosives, explosive devices, improvised explosive devices, chemical warfare agents, industrial and other chemical substances considered hazardous, factors biological, drugs, weapons, radioactive materials and smuggled goods. The invention is an automated system for performing various types of inspections in order to quickly search for more than one dangerous object at a time, in such a way that in a relatively short time many objects can be inspected. In addition, the system of the invention reduces dependence on human operators by utilizing a computational module to achieve this goal, which determines the risk factor based on the simultaneous collection and processing of the results of various studies. In this way, such a system provides a much needed method to increase the accuracy of security checks without adversely affecting throughput. [0016] The term "ionizing radiation test" means in this document any form of test where ionizing radiation is emitted, for example nuclear radiation, X-ray or gamma. Examples of X-ray methods are standard X-ray, backscattering methods, dual or multi-energy methods, as well as computed tomography. Examples of methods that use nuclear radiation sources include thermal neutron analysis (ysis), analysis using pulsed fast neutron analysis, and backscattering technique (ang. backscatter) and the use of terahertz waves. The term "test without the use of ionizing radiation" means methods in which non-ionizing electromagnetic radiation (EM) sources are used, for example those which are subjected to pulsed electromagnetic field and a feedback pulse is obtained. These methods include techniques using wavelengths of many millimeters, magnetic spectroscopy

-4 nuclear resonance (NMR), electron spin resonance (ESR) and nuclear quadrupole resonance (NGR). Terahertz wave generators are an additional potential source of non-ionizing radiation. In addition, "research without the use of ionizing radiation" includes methods used to detect conductive materials in which an object is exposed to electromagnetic fields in the form of continuous or pulsed waves, and detects the appropriate direction of field changes. "Chemical analysis" here means methods for the detection of substances, which include ion mobility spectrometry (IMS), ion mobility spectrometry using ion trap (ITMS), capture detection, chemiluminescence, gas chromatography, measurement of surface acoustic wave parameters, thermal redoximetry, techniques spectroscopic, selective polymer sensors and micro-electromechanical sensors (MEM).

[0017] "Biological classification" means the classification of biological hazards (e.g. organisms, molecules) according to guidelines determining the level of potential hazard associated with toxins, bioregulators and dangerous organisms for epidemiological reasons (e.g. viruses, bacteria, fungi). "Biometric classification testing" includes standard, separate biometric methods, for example fingerprinting, as well as physiological and behavioral parameters that indicate the suspect's behavior.

[0018] The term "simultaneously" means in this document partial or total overlap in time of at least two events of the same or different duration. For example, if event A starts at time 0 and ends at time 10, and event B starts at time 2 and ends at time 10, then events A and B occur simultaneously. Similarly, event C and event D, which both start at time 0 and end at time 7, also occur simultaneously. On the other hand, "sequentially" means that there is no overlap in time of two or more events. If event E starts at time 0 and ends at time 6, and event F starts at time 7 and ends at time 10, events E and F follow sequentially.

[0019] The term "parameter" as used herein includes data and data sets and functions, static or dynamic.

[0020] The term "threat determining function" herein means a defining function or sets of functions defining a state indicating the existence of a threat. Such a function may, or such functions may be a static value or a set of static values ​​or dynamic calculations. This function may, or these functions may be based on certain rules or on a non-heuristic method, for example a neural network.

[0021] The "risk factor" indicates the magnitude of the probability that an object has a security risk. A "set" of risk factors may contain one or more risk factors.

[0022] Fig. 1 is a block diagram illustrating the main components of a multi-threat detection system 10 according to the invention. As shown, this system consists of a control module 20, calculation module 40 and object module 60, which are interconnected. The object module 60 has a mechanism designed to hold the object (e.g. bag or baggage item) being tested. The control module 20 includes various test sources and / or devices, e.g., an x-ray radiation source, chemical analysis apparatus, radio frequency coils and / or other magnetic field inducing devices, when testing without the use of ionizing radiation.

[0023] The calculation module 40, equipped with a processor and memory, is configured to receive input signals from the control module 20 and from the object module 60 and process these signals in order to calculate the risk factor. The risk factor shows the probability that the object in the object module 60 contains a hazardous object. Optionally, there may be a communication assembly in the system, which may include a user interface assembly (not shown) which is connected to the calculation module 40 so that the risk factor and the corresponding warning can be communicated to the system operator according to the invention. [0024] The procedures performed in the control module 20 may now be known tests used to search for dangerous objects, but their scope is not limited to the examples given herein. More than one object module can be connected to control module 20 and calculation module 40, which will allow almost simultaneous control of many objects. [0025] Fig. 2 is a block diagram of an exemplary version of the multi-threat detection system 10.

[0026] The object module 60 has one or more doors 61 through which the object 62 is inserted into the object module 60 to undergo various tests. In some versions of the invention, the object 62 remains stationary on the platform located in the object module 60. In other versions, the object 62 is moved through this module by means of the transport mechanism 67. The transport mechanism 67 is optionally coupled to a gripping mechanism 64, which can be a robotic mechanism capable of holding the object 62 and rotating and positioning it in the desired position at the angle required for inspection. In the embodiment shown, the transport mechanism 67 is a kind of disk system, positioning system Χ-Υ or a combination of both, and is connected to the gripping mechanism 64. In an alternative embodiment, the transport mechanism may be a conveyor belt that moves the object 62 through various inspection stations.

[0027] The object module 60 is equipped with an automated receiver 69, which automatically provides additional information regarding the owner of the object 62. In some embodiments, this data may include information present on the ticket. In other versions, additional information about the owner, for example, his name, citizenship, destination, can also be provided by an automated receiver 69. This receiver can be equipped with a device for digital or magnetic marking, radio frequency marking or other electronic card reader, allowing the identification of the owner or holder of the object 62. Such automatic linking of the object 62 and its owner or holder makes it easier to find a responsible person in when a dangerous item is found. The object module 60 has one or more doors 61 through which the object is removed. In some implementations, door 61 closes automatically when a threat is detected, as part of applicable security procedures.

[0028] In this embodiment, the ionizing radiation control module 20 consists of a subassembly 22 with an x-ray source, a chemical analysis subassembly 30 and a subassembly 36 with a non-ionizing radiation source. X-rays are made using a 24-ray source that emits a beam of light and directs it towards object 62. The X-ray source 24 is preferably located on a rotary mechanism 26 that allows the beam to be directed in different directions because it is often required to adjust the beam direction to the size and position of the object 62. The object module 60 has a series of sensors 66 positioned to receive the beams X-rays after they pass through the object

-662. Additional sensors 66 may also be installed to register diffuse radiation. Based on the received beam, after it passes through object 62, sensors 66 generate output signals and transmit them to the calculation module 40, If x-rays are used in one of the tests, the walls of the subassembly 22 and the object module 60 are shielded so that radiation does not escape outside this object module 60.

[0029] Chemical analysis is performed by taking a sample from object 62 and subjecting it to testing in the chemical analysis subassembly 30. The motion path, given by the displacement device, e.g. rotary displacement device 32, connects the gripping mechanism 64 to the chemical analysis subassembly 30 in such a way that the sample taken from the object 62 can be transported to this subassembly 30. In chemical analysis, for example, ion mobility spectroscopy or newer methods such as selective polymeric sensors and micro-electro-mechanical (MEMs) sensors are used. If ion mobility spectroscopy is used, the chemical analysis subassembly 30 is equipped with an ionization reaction chamber 28. The vacuum pump 33 evokes the air flow needed to obtain a gas sample from the object module 60. The gas sample passes through pipes 32 with adjustable closure, which have gas orifices 63 for collecting gas particles near the object in order to suck in the gas samples. The rotary displacement device 32 and the apertures 63 for collecting particles provide the possibility of mixing the gas in constant contact with it and collecting the particles for continuous analysis as the object moves through the object module 60 and other tests are performed. The sampling openings 63 may be located in a gripping mechanism 64 that moves the object 62 through the object module 60, for example in the robotic arm or belt conveyor mentioned above. The gas sample enters the subassembly 30 for chemical analysis. In an embodiment with ion mobility spectrometry, a gas sample is introduced into the ionization reaction chamber 28 through a rotary displacement device 32 and is ionized by means of an ionizing radiation source. Ionized gas particles are fed to a collecting plate (not shown) located in the ionization reaction chamber 28 by means of the electric power produced in this chamber 28. The number of ions entering the collecting plate is measured as a function of time and this data is sent to the computing module 40 in the form of an output signal or output signals. The microprocessor in the chemical analysis subassembly 30 can convert the number of ions into electrical current and then send that current to the computing module 40. Ion mobility spectrometry (IMS) is a well-known and long-used method.

[0030] Optionally, the chemical analysis subassembly 30 includes a member coupling it to a biological detection system. If such a system is present in the apparatus module 20, the biological class of the object can be determined. A biological detection system that identifies material particles can use one of the methods of chemical analysis. A system whose task is to recognize an organism, for example anthrax, would work on the basis of automated DNA analysis based on automated polymerase chain reaction (PCR), using currently available technology.

[0031] The sub-assembly 36 with the source of non-ionizing radiation, may include a radio frequency source and / or a magnetic field source, for example coils 38 operating in the radio frequency range and antennas for nuclear quadrupole resonance (NQR) and / or eddy current analysis . Such studies provide information on the chemical composition of the object and / or the presence of metal and other conductive materials. The source of the magnetic field can be many sources differing in size and power to detect not only the presence of a dangerous object, but also its

-7umiejscowienie. Radio frequency waves and / or magnetic field are directed at object 62, and sensors 66 receive waves and / or field after or passing through this object 62. For example, if component 36 is a metal detector, it may emit a magnetic field low intensity that object 62 polls as it moves through this field. The transmitter creates a magnetic field that interacts with metal objects in its range, and sensors 66 measure the signal generated by this interaction. Sensors 66 send measurement results to calculation module 40.

[0032] In addition to x-rays, ion mobility spectrometry and testing with a source of non-ionizing radiation in the version according to FIG. 2, any other testing can be used in the system 10 to detect many hazards if it is considered useful in the given conditions. In addition, X-rays, ion mobility spectrometry and a test using a source of non-ionizing radiation can be replaced by other tests deemed appropriate by one of skill in the art. Preferably, each of the components 22, 30, 36 is designed to be independent of the others. Thanks to this, replacing one test with another will probably be a matter of replacing one subassembly with another.

[0033] Sensors 66 may be a matrix of integrated sensors capable of receiving a lot of information in a parallel or multiplex manner. Such sensors are well known. The information collected can be the results of any research, for example, by radio, terahertz, X-ray, gamma, nuclear and chemical analysis, as well as current data.

[0034] The calculation module 40 comprises a processor 42, a memory 44 and a power supply 46. When using the multivariate method, e.g. the method described below with reference to Fig. 3, the calculation module 40 determines the risk factor, indicating the probability of being in the object of the dangerous object. The calculation module 40 is equipped with a communication connector 50, through which it sends optical ΐ / or acoustic warnings, by any means of communication, preferably wirelessly, if it deems probable that there is an object of danger in the object. In addition, at least one open interface 95 is available that allows the computing module 40 to connect to another device, e.g. a gateway control platform for people control or a processing platform for incoming biometric data. The open interface 95 can allow to connect, wired or wirelessly, with such other devices.

[0035] The results of the chemical analysis can be sent directly to the calculation module 40 from the collecting plate in the chemical analysis subassembly 30. If necessary, however, data from the collecting plate can be indirectly transmitted to sensor or sensors 66, in the object module 60 and then from sensor / sensors 66 to the calculation module 40. If other methods, e.g. passive sensors are used, the particles can be directed directly to sensors 66. Other data, for example x-ray data, is received by sensors 66 and sent to calculation module 40. The term "sensors" here means any type of device capable of performing physical or electrical measurements and generating an output signal for calculation module 40, for example sensors 66 in object module 20 and collecting plate in subassembly 30 for chemical analysis.

[0036] Although Fig. 2 shows the control module 20, the calculation module 40 and the object module 60 as three separate elements, this division is illustrative, whereas the physical modules do not necessarily correspond to such a conceptual division. All three modules can be located on

- example in one housing, or control module 20 and object module 60 in the same housing, and calculation module 40, in another place.

[0037] Fig. 3 is a block diagram showing the sub-modules of the calculation module 40 for implementing the method for identifying a hazardous object. As stated above, the computing module 40 receives input signals from the control module 20 and / or the object module 60. These input signals are derived from raw data received by sensors 66 ί / or a collecting plate in ion mobility spectrometry (or other chemical sensor). As shown in the diagram, the method of the invention uses a set of functional sub-modules 116, 118, 120, 122, 124, 126, 128, 206, 208 to process various input signals from the sensors 66 and the sensor in the control module 20 (e.g. collecting plate). These sub-modules calculate the values ​​of a series of parameters for object 62, e.g. texture, density, electrical conductivity, molecular classification, location classification, radiation classification, visual classification, biological classification, biometric classification, if object 62 is, for example, a bag that contains many elements, then these elements can be automatically sorted depending on texture, density, conductivity etc. so that each element is classified separately. [0038] In the specific version of Figure 3, methods for identifying a hazardous object, the results of active (e.g. X-ray) radiation detection are used to perform texture classification, density classification, shape context classification, location classification and visual classification. In order to classify radiation, the radioactivity level of an object can be determined. For texture classification, conductivity classification, location classification and other parameters, current data or response signals to the induced electromagnetic field are used. The reaction to the magnetic field is used to perform molecular classification, density classification, location classification and other parameters. The molecular classification uses the result of any chemical analysis. The output signals from the sensors 66 and the output signals from the chemical analysis subassembly 30 are sent to different sub-modules in parallel so that the values ​​of all parameters in classification areas, e.g. textures, densities, are calculated simultaneously or almost simultaneously.

[0039] After determining the parameters based on the values ​​and functions for each of these classification areas, the values ​​are processed collectively in the sub-module 300 of the multi-variable data matrix and a risk factor is calculated. The multi-variable data matrix module 300 arranges the classification parameters from the function matrices 116, 118, 120, 122, 124, 126, 128, 206, 208, 210 into an n-dimensional data matrix. For example, the matrix 124 of the visual classification function generates a series of visualization data [V] as a function of the number in the range and the measured angle (Φ), depending on the number of revolutions of the gripping mechanism 64, so one form of data processing is the function V = f (<t >) n. In addition, a series of visualization data [V] related to density parameters [D], at all angles Φ, gives a set of parameters V - f (D, Φ, n). Another set of parameters introduced into the matrix of multivariable data 300 are conductivity classifications derived from matrix 120 of conductivity classification functions; similarly, they provide a number of interrelated parameters, for example information about conductivity [Z], characterized by the value (i) changing as a function of location (I), giving one set Z = f (i, I). These three examples of functions, i.e. V = ί (Φ, /?), V - f (D, Φ, n) and Z - f (i, I), are to be ordered in a matrix of 300 multi-variable data in such a way, to create multiple attributes for a given spatial location, as well as global attributes for the entire controlled

-9 object, More generally, all sides of the classification function matrix will give multiple sets of parameters to create an n-dimensional matrix of parameters for processing in block 310.

[0040] The n-dimensional matrix of parameters generated in block 310 makes it possible to perform many calculations in this block and to process dependent and mutually dependent parameters. Parameters from the sub-module 300 of the multi-variable data matrix are passed to the threat determination functions for which hybrid calculation sets are performed. Hybrid calculations include combinations of rule-based and non-heuristic methods (e.g. neural networks or other algorithms using artificial intelligence) and comparing the result with criteria and conditions from practical knowledge (block 310). In some versions, an example of a rule-based decision is to compare some or all parameters together with threshold values. For example, the condition 'If texture classification Τ (Φ, L) n> 3, density classification D (<ł>, L) n> 4, conductivity classification Z (i, l) n> 4, location classification> 3 and radiation classification > 1 ", can be used as a condition for determining one type of risk factor and possibly generating a warning. The calculations can include any simple or complex combination of individual parameter values ​​calculated in decision block 310 to determine sets of risk factors. The sets of risk factors correspond to different categories of hazards that are likely to occur at the site. For example, there may be a category of hazard functions related to the likelihood of a biological event that generate a certain risk factor for such a category, there may be a category of hazard functions associated with the likelihood of a hazard of explosives generating a certain risk factor for the category of explosives, as well as there may be a category of hazard functions related to the overall probability resulting from a combination of attributes that are not necessarily specific to the type of material, Different calculations may give more than one risk factor in each category. Hazard functions include test conditions and include criteria based on previously gained practical knowledge of signals and combinations of signals that indicate hazards.

[0041] If the risk factor is so high that the predefined condition dfa of the set of threat thresholds is met, the location, amount and type of the dangerous object, depending on the system version, can be estimated (block 320), and a warning ( block 330). Whether the risk factor is high enough to give a warning depends on the sensitivity settings in the system, with a default setting that the user can change. The "warning" can be an optical or acoustic signal, notifying the operator of the detection of a potentially dangerous object, and also entails taking other actions, e.g. closing or blocking the door 61 of the object module 60. Optionally, a signal is sent (e.g. green light), which indicates that the object is free of objects that pose a security risk (block 325).

[0042] Fig. 4 shows an embodiment of the multi-threat detection system 10, consisting of a single control module 20 and five object modules 60a-60e. As shown, the control module 20 is centrally positioned relative to the object modules 60, whereby the object is checked by the control module 20 regardless of which object module it is in. An advantageous solution is to place in the control module 20 a rotating mechanism enabling a change of direction, for example, of an analytical beam depending on which object is to be checked. When all the field modules are full, the control module executes

-10 examining objects, rotating step by step between individual object modules 60, as shown by arrows. Some tests are carried out sequentially, for example by X-ray, the radiation beam is directed from the control module 20 in turn to the object modules 60a-60e, and the order can be predetermined. Other tests, however, for many object modules 60a-60e, are performed simultaneously, for example in chemical analysis, a sample of each object can be taken at the same time from all object modules 60a-60e, because each object module has its own rotary displacement device 32 , gripping mechanism 64 and particle collection openings 63. Thus, depending on the tests provided for in a given version of the system, the test (as a whole) with five object modules 60a-60e, may be partly sequential and partly simultaneous. All test data is sent to calculation module 40, preferably immediately after it is obtained.

[0043] The output signals from the sensors 66 (and the collecting plate in the chemical analysis subassembly 30, if present) can be processed by a single calculation module 40 or by more than one such module. If there is only one calculation module 40, it separates objects to provide five different results, one for each object 62.

[0044] The embodiment according to Fig. 4 allows for fast data processing compared to the current security control system in which passengers line up and objects (e.g. suitcases) are checked at this time. Thus, all tests grouped in the control module 20 can be carried out in the object modules 60a-60e simultaneously for each of the objects, so that the flow of passengers is not hindered.

[0045] The multi-threat detection system 10 of Fig. 4 can be designed as a modular system so that the number of object modules 60 can be changed as desired. Thus, if in one area the movement of people is large and the other area has decreased, several object modules from this second area can be moved to the first area by simply disconnecting them from one control module 20 and connecting them to another control module 20. Such flexibility gives additional cost savings for public entities that would use the multi-threat detection system 10. The object modules 60a-60e are substantially identical to each other.

[0046] In addition, the platform on which the object 62 is placed in the object module 60 may be equipped with a sensor, e.g. a weight sensor, which transmits to the control module 20 a signal informing whether a given object module 60 is currently in use, or not. So if for some reason only the 60a, 60b, 60d and 60e object modules are used, then the control module 20 will not unnecessarily send analytical beams and take samples from the empty object module 60c, and the system 10 will automatically optimize the testing procedures.

[0047] In this particular embodiment of the system, modules having a hexagonal shape are shown to create a honeycomb configuration - however this is only an example and not a limitation of the invention. [0048] Fig. 5 is a block diagram illustrating a control module 20 and object modules 60a-60e. In this particular version, a single calculation module 40 works with all 60a-60e object modules. Each of the object modules 60a-60e has a transport device, e.g. a mechanical mechanism, multi-axis manipulator, robotic mechanism or belt conveyor, and a sensor matrix as described above with reference to Fig. 2. The control module 20 consists of four components: subassembly with ionizing radiation source, chemical analysis subassembly, non-ionizing radiation subassembly and field induction subassembly

-11magnetycznego. Each of the object modules 60a-60e is connected to the control module 20 and calculation module 40.

[0049] Fig. 6 shows another exemplary embodiment of the multi-threat detection system 10 where the object is a human (or any animal). In the specific embodiment shown, object modules 60a, 60b are attached to the control module 20. Obviously, tests using radiation should be carried out with caution, choosing appropriate radiation parameters, especially if the tested "objects" are people. If desired, an object recording camera can be installed in the control module 20 or in the field module 60a and / or 60b in a suitable location to biometrically classify and / or send images to the operator.

[0050] Fig. 7 shows yet another embodiment of the system 10 for detecting multiple threats, in this version for checking inanimate objects and people. This particular version is characterized by a control module 20 with five object modules 60a-60e intended for testing inanimate objects and a gate 60f through which people or animals pass. The control module 20 examines objects and people in each of the 60a-60f object modules. In certain situations where the object module 60f is too far from the control module 20, a separate control module can be provided for the object module 60f. However, all object modules and both control modules will still send signals to one calculation module 40.

[0051] The invention allows detection of threat objects with increased accuracy compared to the system currently available. The current systems use a sequence of separate devices, each of which performs only one test and generates a result based on this one test, while the system according to the invention takes into account a combination of many parameters. Due to this, when a bomb with a low explosive content and a low mass of conductive material can not be detected by the current system, because both materials are present in quantities lower than the threshold values, such an object could be "caught" by the system according to the invention, because the presence of a certain a combination of indicator materials and proximity parameters included in the hazard determination functions could trigger an alarm. The use of a combination of parameters provides greater flexibility and increased accuracy in detecting the presence of objects that threaten security.

[0052] The invention further allows the detection of a non-specific threat item. It differs from the current system, focused on specific objects and materials, for example, explosives, drugs, weapons, etc. By detecting the occurrence of a general combination of potentially hazardous materials, the system according to the invention makes it difficult to pass through the security control system of new, ingeniously constructed, objects dangerous.

[0053] Although the above refers to particular embodiments of the invention, it should be understood by those skilled in the art who make changes to this embodiment that they cannot fall outside the scope of the invention as defined in the appended claims.