System and method for detecting objects

Abstract

The present teachings relate to methods, systems, media, and implementations for detecting an electronic target object. A magnetic field is first generated. Magnetic field variations associated with the presence of an object in the vicinity of the magnetic field are observed and analyzed to extract features characterizing the magnetic field variations. Based on such extracted features, it is determined whether the object corresponds to the electronic target object. If so, an alarm is triggered to indicate that the electronic target object is detected.

Description

[0001] Cross Reference to Related Applications

[0002] This application claims priority to U.S. Provisional Application No. 62 / 825,454, filed March 28, 2019, and U.S. Provisional Application No. 62 / 825,407, filed March 28, 2019, the contents of which are incorporated by reference in their entirety. TECHNICAL FIELD

[0003] The present teachings relate generally to security. More particularly, the present teachings relate to security via detection of target objects. BACKGROUND

[0004] Security is an important aspect of daily life that safeguards the public. This is especially true in public gathering places such as public transportation sites (e.g., airports, train stations, bus stations, etc.), conferences, and the like. Security doors are a security screening means often deployed at, for example, the entrance points of airports, train stations, government offices or companies, cruise ships, and the like to detect metal objects that can be used as weapons. Security doors are often deployed in places with high human traffic (e.g., airports, conferences, or cruise ships). One example security door is shown in FIG. 1 (Prior Art). As shown, the example security door 100 is shaped as a door with two vertical columns 110-1 and 110-2 and a ceiling portion 120. For security screening, detection devices can be embedded and deployed in the security door to detect certain specified objects. For example, security doors currently installed in public places can detect metal objects such as guns, knives, or scissors. When a person being screened for security walks through the security door 100, if the person carries a metal item, the security door will sound an alarm.

[0005] With the advancement of such detection and the reliability of such detection, methods of concealing harmful objects have also been developed. For example, instead of metal objects, some criminals can find ways to use electronic devices as potential weapons by incorporating attack means in such electronic devices (including laptops, tablets, phones, or even very small electronic devices). Currently, while security doors can be used to detect the presence of metal objects in a non-contact manner, they cannot detect the presence of electronic devices.

[0006] Accordingly, there is a need for methods and systems that address such limitations. SUMMARY

[0007] The teachings disclosed herein relate to methods, systems, and programming for data processing. More particularly, the teachings relate to methods, systems, and programming related to modeling a scene to generate scene modeling information and utilization thereof.

[0008] In one example, a method for detecting an electronic target object implemented on a machine having at least one processor and a communication platform capable of connecting to a network. A magnetic field is first generated. Magnetic field variations associated with the presence of an object in the vicinity of the magnetic field are observed and analyzed to extract features characterizing the magnetic field variations. Based on the features thus extracted, it is determined whether the object corresponds to an electronic target object. If so, an alarm is triggered to indicate that the electronic target object is detected.

[0009] In a different example, the present teachings disclose an apparatus for detecting an electronic target object. The apparatus comprises a magnetic field generation unit, one or more sensors, a signal processing unit, and an alarm triggering unit. The magnetic field generation unit is configured for generating a magnetic field. The one or more sensors are configured for sensing magnetic field variations associated with the presence of an object in the vicinity of the magnetic field. The signal processing unit is configured for extracting features characterizing the magnetic field variations and determining whether the object is an electronic target object based on the features thus extracted. The alarm triggering unit is configured to trigger an alarm in response to the detection if an electronic target object is detected.

[0010] Other concepts relate to software for implementing the present teachings. A software product according to this concept comprises at least one machine-readable non-transitory medium and information carried by the medium. The information carried by the medium can be executable program code data, parameters associated with the executable program code, and / or user-related information, requests, content or other additional information.

[0011] In one example, a machine-readable non-transitory and tangible medium has information recorded thereon for detecting an electronic target object. When the information is accessed by a machine, it causes the machine to perform a series of steps. A magnetic field is first generated. Magnetic field variations associated with the presence of an object in the vicinity of the magnetic field are observed and analyzed to extract features characterizing the magnetic field variations. Based on the features thus extracted, it is determined whether the object corresponds to an electronic target object. If so, an alarm is triggered to indicate that the electronic target object is detected.

[0012] Additional advantages and novel features will be set forth in part in the description that follows, and in part will become apparent to those skilled in the art upon examination of the following and the accompanying drawings or can be learned by production or operation of the examples. The advantages of the present teachings can be realized and attained by means of the instrumentalities, combinations and methods particularly pointed out in the detailed examples discussed below. BRIEF DESCRIPTION OF DRAWINGS

[0013] The methods, systems, and / or programs described herein are further described by way of exemplary embodiments. These exemplary embodiments are described in detail by reference to the drawings, which are to be considered in conjunction with the detailed description. These embodiments are non-limiting examples in which like numbers indicate like structural elements throughout the several views of the drawings, and in which:

[0014] Figure 1 (prior art) illustrates a conventional security door with a post;

[0015] Figure 2A depicts an exemplary configuration of a security post according to embodiments of the present teachings;

[0016] Figure 2B depicts a high level system diagram of a segment of a security post according to embodiments of the present teachings;

[0017] Figure 2C is a flowchart of an exemplary process for a segment of a security post according to embodiments of the present teachings;

[0018] Figure 2D shows an exemplary implementation of a segment of a security post according to embodiments of the present teachings;

[0019] Figure 2E shows an alternative implementation of a segment of a security post according to embodiments of the present teachings;

[0020] Figure 3A shows an exemplary configuration of different parts of a security post according to embodiments of the present teachings;

[0021] Figure 3B shows an exemplary assembly of different parts of a security post according to embodiments of the present teachings;

[0022] Figure 3C shows an alternative configuration of different segments of a security post according to embodiments of the present teachings;

[0023] Figure 4A shows an exemplary internal implementation of a segment of a security post according to embodiments of the present teachings;

[0024] Figures 4B-4D illustrates an exemplary implementation for attaching adjacent segments of a security post according to embodiments of the present teachings;

[0025] Figures 5A-5E depicts an exemplary deployment of security post(s) according to embodiments of the present teachings;

[0026] Figure 6A shows the types of objects to be detected using a security post and the means of detecting them according to embodiments of the present teachings;

[0027] Figure 6B depicts an exemplary high level diagram of a security post connected to a server via a network connection according to embodiments of the present teachings;

[0028] Figure 6C is a flowchart of an exemplary process for a security post according to embodiments of the present teachings;

[0029] Figure 6D is an exemplary distribution characterizing the magnetic field variation caused by the presence of a metallic object and an electronic object;

[0030] Figures 6E-6F illustrates exemplary thresholding criteria for classifying metallic and electronic objects according to embodiments of the present teachings;

[0031] Figure 7A depicts an exemplary high-level architecture of a system in a security column for detecting metallic / electronic objects according to embodiments of the present teachings;

[0032] Figure 7B shows different types of information that a security column can extract in order to detect different types of information according to embodiments of the present teachings;

[0033] Figure 7C shows different types of models that a security column uses to detect different types of information according to embodiments of the present teachings;

[0034] Figure 8A depicts an exemplary high-level diagram of a system in a security column for detecting metallic / electronic objects according to embodiments of the present teachings;

[0035] Figure 8B is a flowchart of an exemplary process of a system in a security column for detecting metallic / electronic objects according to embodiments of the present teachings;

[0036] Figure 9 is an illustrative diagram of an exemplary mobile device architecture that can be used to implement a special-purpose system embodying the present teachings according to various embodiments; and

[0037] Figure 10 is an illustrative diagram of an exemplary computing device architecture that can be used to implement a special-purpose system embodying the present teachings according to various embodiments. DETAILED DESCRIPTION

[0038] In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the relevant teachings. However, it will be apparent to one skilled in the art that the present teachings can be practiced without these details. In other instances, well-known methods, procedures, components, and / or circuitry have been described at a relatively high-level, without detail, in order to avoid unnecessarily obscuring the relevant teachings.

[0039] The present teachings aim to address the deficiencies of conventional security columns for detecting metal objects. In particular, the present teachings disclose a security column capable of detecting the presence of either metal objects or electronic devices. In some embodiments, the present teachings disclose not only detecting the presence of metal substances with complex compositions, but also accurately distinguishing whether the detected metal substances are mixed with metal scrap or electronic devices. That is, via analysis of signals such as certain patterns of magnetic field changes caused by the detected metal, it can be determined whether electronic devices are present. In some embodiments, the presence of electronic devices can also be detected via communication means. Once a mixture of metals that can be indicative of the presence of electronic devices is detected, one or more communication signals in compliance with certain corresponding protocols can be transmitted within a configured range. If a response signal is received, the presence of electronic devices is confirmed.

[0040] In some embodiments, the security column according to the present teachings is assembled with different segments, each of which is independently configured to detect metal or electronic objects. Since different segments of the security column correspond to different heights, the segment detection enables more precise identification of the location of the detected metal / electronic objects. Each segment can include its own detection means and alarm means, such that an alarm can be triggered upon detection of metal / electronic objects. In some embodiments, one of the segments of the security column according to the present teachings can include a display screen for displaying detection information and providing an interface for a user to specify or set operational parameters to be used by different segments to function. In some embodiments, detection of metal objects can be performed independently by each segment, and detection of electronic objects can be performed in an integrated manner based on metal detection signals from different segments. In some embodiments, the detection results can be sent to a server located elsewhere for, e.g., centralized control and data logging.

[0041] In some embodiments, the security column according to the present teachings can also be configured to activate means for acquiring additional information related to the surroundings of the detection upon detection of either metal objects or electronic objects. Such additional information can include surroundings information such as physical, emotional, behavioral or spatial information associated with the detection and biometric information such as facial information, either acquired from sensors or analyzed based on sensor data. Such additional information provides useful contextual information for the detected metal / electronic objects and the person hiding the detected metal / electronic objects.

[0042] Figure 2A An exemplary configuration of a security column 200 according to an embodiment of the present teachings is depicted. As shown in this embodiment, the security column 200 is assembled using different segments, including an upper segment 210-1, a middle segment 210-2, and a lower segment 210-3. In some embodiments, each segment is a segmented cylinder plus a threaded connection structure, as will be described with reference to FIG. 2B. Figures 3A-3C andFigures 4B-4C The safety post 200 also includes an integral alarm light 210-4, which may have a ring shape or any other suitable shape. The safety post 200 also includes a base 210-5 attached to the stand 210-6. Although Figure 2A The diagram shows three distinct sections, but different configurations can be implemented. For example, there could be two sections. As another example, there could be more than three sections. The specific implementation can depend on the deployment of the safety pillars. For instance, if safety pillars are used in a setup where people at different heights can pass through, the safety pillars can be quite tall, allowing for the assembly of more sections to detect metal / electronic objects that people at different heights might be carrying.

[0043] Generally, a security gate is a metal detector. It relies on the principle of electromagnetic induction. That is, when an alternating current passes through a coil, it generates a rapidly changing magnetic field. When a metallic object is present, this magnetic field induces eddy currents within the metal object. These induced eddy currents also generate a magnetic field, which in turn affects the original magnetic field created by the coil. This change in magnetic field can then be used to detect the presence of a metallic object. A specific frequency, such as 80-800 kHz, is typically used to generate the magnetic field. Magnetic fields of different frequencies are known to be suitable for detecting different types of target objects. For example, lower operating frequencies provide better detection performance for iron-based objects, while higher operating frequencies provide better detection performance for objects made of high-carbon steel.

[0044] In some embodiments, each segment is configured to independently detect metallic or electronic objects. Figure 2B A high-level system diagram depicts a segment (e.g., 210-1) of a safety pillar 200 according to an embodiment of this teaching. Each segment includes several functional modules to enable detection. Figure 2B As shown, the segment includes a magnetic field generation unit 201, a sensing section 202, a signal processing unit 204, and a segment alarm unit 206. The magnetic field generation unit 201 is configured to generate a raw magnetic field and detect changes in that raw magnetic field. In some embodiments, depending on application requirements, the magnetic field generation unit 202 may also generate more than one magnetic field, each with different parameters (such as operating frequency), to enable the detection of different types of target objects.

[0045] Sensing section 202 is provided to detect any changes in the original magnetic field and may include one or more sensors deployed to sense information related to changes in the magnetic field caused by, for example, metal. The sensors to be used can be any sensors that can be used to detect information related to the presence of metal or a mixture of metals. For example, such sensors may include fluxgate sensors designed to detect the presence of metallic substances. This sensed information can then be analyzed by signal processing unit 204 located in the same section to determine the presence of a target object based on the sensed changes in the magnetic field. If a target object is detected via signal processing, section alarm unit 1 206 in section 210-1 triggers an alarm associated with that section.

[0046] Figure 2C This is a flowchart illustrating an exemplary process of a segment of a safety post 200 according to an embodiment of this teaching. To enable detection, a magnetic field generation unit 201 is activated to generate a magnetic field at 225 according to some predetermined parameters. Such parameters may include frequency, etc., and may be determined based on the needs of a specific application (e.g., a specific type of target object to be detected). To detect a target object, a sensing segment 202 is activated at 230 to sense information related to changes in the magnetic field caused by the presence of metallic material. The sensed information can then be sent to a signal processing unit 204 at 240. Upon receiving the sensed information, the signal processing unit 204 analyzes the information associated with the magnetic field and its changes at 250 to determine, at 260, the presence of a metallic or electronic object based on features detected from the sensed changes in the magnetic field. When the presence of a metallic and / or electronic object is determined, a segment alarm unit 206 is activated to trigger a segment alarm as a report.

[0047] While each segment of the illustrated embodiment has its own magnetic field generating unit, it is also possible to have a unified magnetic field generating unit for the entire safety column to generate a magnetic field that can be relied upon by all segments of the safety column. In some embodiments, it is also possible for the magnetic field generating unit to generate multiple magnetic fields, each with different parameters (such as operating frequency) and used for different groups of objects. Such multiple magnetic fields can be generated simultaneously or according to a time-switching schedule, such that different magnetic fields are generated and used to detect a specified group of objects at different time intervals during the time-switching schedule. When using a time-switching schedule, signal processing units located in different segments can also be managed to operate synchronously according to the time-switching schedule to detect different target objects during such time slots.

[0048] Figure 2DAn exemplary embodiment of a segment of a safety post 200 according to an embodiment of this teaching is shown. In this exemplary embodiment, the segment shown is, for example, the upper segment 210-1, embedded with various parts such as a sensing part 202, a signal processing unit 204, and a segment alarm unit 206. Notably, this exemplary embodiment also includes a segment alarm 208, which may correspond to a light, a speaker, or a combination of both, such that when a metallic / electronic object is detected, the segment alarm unit 206 can be triggered to activate the segment alarm 208 to report the detected metallic / electronic object. The segment also includes a connection structure 207 at the bottom, which may correspond to a male or female threaded connector to connect to a matching female or male threaded connector of another segment to form a secure connection. Depending on the configuration, when a detection is reported, the light may be turned on (it may be static or flashing), a specific sound (e.g., a siren) may be broadcast, or a combination of both light and sound may be activated to report the detection.

[0049] Figure 2E Alternative implementations of sections of the safety post 200 according to embodiments of this teaching are shown. As discussed herein, the upper section 210-1 is shown. In this embodiment, in addition to the sensing section 202, signal processing unit 204, section alarm unit 206, and alarm light 208 implemented therein, there is a touch-sensitive display screen 212 implemented on the upper section. This touch-sensitive display screen can provide an interface for displaying detection results to a user (e.g., a TSA officer at an airport) and allowing the user to specify various parameters to be used to operate the safety post via the touchscreen. For example, the interface can be used to display detection results from different sections in some form. For example, the interface can be configured to display the most important detection results associated with a specific section. It can also be configured to display detection results from all sections simultaneously. Various layouts are available for displaying detection results, and the user can choose to use one of these layouts to display the detection results. Although in... Figure 2E In the illustrated embodiment shown, a touch display screen is located on the upper section 210-1, but it can also be implemented on different sections of the safety column.

[0050] The display screen can also serve as an interface allowing users to interact with the detection system to specify operating parameters. Some of these parameters can be related to the sensitivity of detection, such as the detection of metallic / electronic objects. Others can relate to how to warn the user of detected metallic and electronic objects. For example, different colors can be assigned to zonal alarms to indicate different types of detection results or different degrees of certainty, such as the detection result's certainty. Parameters such as the confidence level of the detection result determine the alarm's loudness.

[0051] Each section of the safety pillar 200 disclosed herein can be manufactured separately and then assembled to construct the pillar 200. Figure 3A Different sections of a separately manufactured safety post 200 according to an embodiment of this teaching are shown. As can be seen, each section is a separately manufactured article of manufacture and they can be connected using, for example, an exemplary male / female threaded connector, such as... Figures 4A-4C As disclosed in the document. Figure 3B An embodiment of the present teaching is shown using, as Figure 3A The exemplary safety post 200 shown is assembled together by a connection structure (such as a male / female threaded connector). Figure 3C Alternative arrangements of different sections of the safety pillar 200 according to embodiments of this teaching are shown. As can be seen in the figure, Figure 3A and Figure 3C The difference lies in the touchscreen display. Figure 3A In the upper section 210-1, while Figure 3B The middle section 210-2 is located in the middle section. In the illustrated embodiment, each section is a cylinder with a threaded connection structure that securely connects adjacent cylinders together. This embodiment is for illustrative purposes only and is not intended to be limiting. Other structures may also be used for each section, and corresponding connection structures may be appropriately deployed to securely fasten adjacent sections together to form a safety post consistent with this teaching.

[0052] Figure 4A An exemplary internal implementation 400 of a segment of a safety pillar 200 according to an embodiment of this teaching is shown. The exemplary implementation 400 is deployed within each segment of the safety pillar 200 and includes, as... Figure 2B The implementation of different functional modules disclosed herein. Specifically, implementation 400 includes a board 410 on which various parts are implemented to perform functions corresponding to sensing segment 202, signal processing unit 204, and segment alarm unit 206. As shown in the figure, as an example, it includes a fluxgate sensor 420, a signal processing board 430 on which one or more sensing means (such as fluxgate sensor 420) are mounted, and the signal processing board 430 implements the functions of signal processing unit 204 and segment alarm 485. There are also wires 450 that connect fluxgate sensor 420 and signal processing board 430, and connect to adjacent segments via PCB board 470 so that signals can be transmitted within or between segments. There are also other power lines 435 that deliver power to different parts on board 400 and to adjacent segments via PCB board 470. At one end of board 410, there is a connector 480 for connecting PCB board 460, which connects to another adjacent segment to reference Figures 4B-4D The connection structure for receiving power is discussed in detail.

[0053] Figures 4B-4D An exemplary embodiment of a connection structure for attaching adjacent sections of a safety post 200, according to an embodiment of this teaching, is illustrated. Figure 4B The PCB board 460 of section 210-1 is shown (also in Figure 4A (middle) is attached to the segment via, for example, connector 480. To connect segment 210-1 to another segment, segment 210-1 has a... Figure 4C The female connector 490-2 in section 210-1 is matched with the male connector 490-1. When the male connector 490-1 in section 210-1 matches the female connector 490-2 in the adjacent section, the conductive concentric circle contacts on the PCB board 460 are... Figure 4B The spring pin 492 shown is used to transmit power and other signals from the connected section to section 210-1 via the spring pin 492 and the conductive connection circle on the PCB board 460.

[0054] In some embodiments, in addition to the male and female connectors connecting the two sections, there are additional means to secure the connection between the two adjacent sections. For example, in Figure 4B In the middle, there is a hole 465-1 through which a fastening means, such as a nail, can be driven to secure the connection between the two sections. Through this hole, when using a fastening means (e.g., driving), the fastening means can protrude into the interior of the female connector 490-2, such as... Figure 4C 465-2. That is, the connection structure between the base 207 and each section of the safety post uses a male / female threaded connector connection structure. The electrical connection between sections is made through a spring ejector and a ring-shaped PCB board. This is in Figure 4D As shown in the diagram, each section has a segmented structure. That is, a nested series structure is applied outside the pre-installed circuit board. The segmented body of the safety post and the terminal joints between adjacent sections ensure maximum structural rigidity and tightness of the joints.

[0055] The safety post 200 disclosed herein can be used in various applications. It can be deployed as a post or used in different ways to form a security door. Figures 5A-5E An exemplary deployment of one or more safety pillars according to embodiments of this teaching is depicted. Figure 5AIn this system, a safety gate 500 is constructed using two safety pillars 510 and 520 and a top structure 505. Each of the safety pillars 510 and 520 is similarly configured to have multiple sections. As shown, safety pillar 510 has an upper section 510-1, a middle section 510-2, a lower section 510-3, an overall alarm 510-4, and a base 510-5. Similarly, safety pillar 520 has an upper section 520-1, a middle section 520-2, a lower section 520-3, an overall alarm 520-4, and a base 520-5. When a person passes through the safety gate, at least some of the sensing portions in the different sections of safety pillars 510 and 520 sense relevant information for detecting metallic / electronic objects and send this sensed information to their corresponding signal processing units to detect the signal characteristics (signature) of the metallic and electronic objects. If a section within a safety column detects the presence of a metallic or electronic object, the section alarm unit can trigger a local alarm located within that section, indicating the location of the detected object. It can also trigger the overall alarm to indicate the detection of a suspicious object.

[0056] Figures 5B-5C Different configurations of security doors according to embodiments of this teaching are shown. In these embodiments, security door 530 is configured to use a security post on one side while the other side has only a post without detection means and alarm. Figure 5B An exemplary security door 530 is shown, which has a single security post 520 on the right side and a regular post 535 with a base 535-1 on the left side. Figure 5C Another exemplary security door 540 in the opposite configuration is shown, having a single security post 510 used on the left and a regular post 550 with a base 550-1 on the right. Both configurations have a top 505 to form the security door. In some embodiments, the top 505 may be omitted, allowing the two posts on either side to form a security check path (without a top). Figures 5A-5C Any of the exemplary security doors 500, 530 and 540 shown can also have a corresponding variation without a security path at the top 505. Figure 5D An example security path 560 shown is configured based on a security door 540 with the top 505 removed. In some embodiments, a column that does not have means for detecting metallic / electronic objects may also be equipped with devices for detecting other substances / objects, such that the security door or security path thus formed can be configured to detect multiple types of objects / substances carried by a person passing through the door / path.

[0057] Figure 5EAnother application of the security post according to an embodiment of this teaching is illustrated. In this illustrated embodiment, the security post 510 is used in conjunction with an access gate controller 590 to control entry via door 580 based on detection results from the security post 510. In this application, when a person intending to pass through door 580 approaches door 580, the security post 510 detects whether the person is carrying or concealing a metal or electronic object. If no metal / electronic object is detected from the person, the security post 510 can wirelessly notify the access gate controller 590, which can then control door 580 to open to allow the person to pass. On the other hand, if a suspicious object, or a metal or electronic object, is detected, the security post 510 notifies the access gate controller 590 not to open door 580 to deny entry.

[0058] This article has discussed various embodiments of safety posts in terms of their physical construction or composition. The following discussion concerns the functional aspects of the safety posts to achieve the intended purpose of detecting metallic and / or electronic objects. Figure 6A This document summarizes the types of objects detected using safety posts according to embodiments of this teaching and the means of detecting them. The types of objects to be detected according to this disclosure include metallic objects and electronic objects. Detection of both types of objects is based on magnetic information sensed when a person passes by. Regarding detection, the presence of metallic substances with complex compositions can be detected based on changes in the magnetic field caused by the metal. Comparing metallic and electronic objects, metallic objects can contain a large amount of metal, while electronic objects can contain metal mixed with other substances, thus with a much lower content. For example, electronic devices can have a limited number of metal-containing components, such as coils, metal wires in circuit boards, etc. Therefore, the key to distinguishing between metallic and electronic objects is detecting the difference in magnetic field changes caused by the presence of metal. This is achieved by analyzing the nature or characteristics of the magnetic field changes caused by the presence of metal in either the metallic or electronic object. This is in... Figure 6A This is listed as one method for detecting electronic objects. Another alternative method for detecting electronic objects is via communication means, such as... Figure 6A As shown in the diagram. This method is used to detect activated electronic objects or devices. The details of detecting such anticipated objects are discussed below.

[0059] Figure 6BAn exemplary high-level system diagram is depicted of a security column 210 connected to a server 650 via a network connection 640 according to an embodiment of this teaching. In this illustrated embodiment, the security column 210 includes multiple sections (e.g., sections 210-1, 210-2, and 210-3), section alarms associated with their respective sections (i.e., section 1 alarm 208-1, section 2 alarm 208-2, and section 3 alarm 208-3), a central controller 600, and an overall alarm 210-4. Alternatively, each section may include its own magnetic field generating unit (e.g., as discussed herein). Figure 2B (as shown in the diagram), or there is a unified magnetic field generating unit (not shown). In some embodiments, each segment in the safety column 210 independently detects the presence of metallic and / or electronic objects. If a segment detects a target object, then the segment alarm unit of that segment triggers its associated segment alarm. In some embodiments, each segment may collect and process information sensed by sensors located in that segment and send such processed information to a unified signal processing unit, where information from different segments may be integrated to make an overall determination about the presence of a target object.

[0060] The central controller 600 handles safety column-level operations. It includes a signal integration unit 610 and a display screen 212 (see [link]). Figures 3A-3C The system includes an alarm triggering unit 620. Each segment can send its detection results or processed information to a signal integration unit 610, which integrates the segment results and determines whether a target object has been detected. When a target object is detected, the signal integration unit 610 can activate the alarm triggering unit 620 to trigger the overall alarm 210-4. In some embodiments, each segment can be flexibly configured to simply process the sensed information to forward or determine, for example, whether metal is present within the vertical range specified for that segment and whether the detected object is a metallic or electronic object. When the signal integration unit 610 needs to determine a target object, it can integrate information from different segments to assess, for example, the presence or location of a metallic or electronic object based on a detailed analysis of magnetic field variations. In some embodiments, the signal integration unit 610 can also function as a controller coupled to the display screen 212 to receive operating parameters such as a user-specified sensitivity level and transmit such operating parameters to different segments to facilitate their respective operation.

[0061] In some embodiments, security posts, whether operating independently or within a larger structure (such as a security door), can operate as distributed units and connect to a server located elsewhere, transmitting their detection results to the server. This can be supplemented by recording detected events on their own local storage device (not shown). In this case, signal integration unit 610 can transmit certain information to server 640 via network 630. In some embodiments, in addition to the detection results of metallic or electronic objects, other types of information associated with a person carrying the detected metal or electronic device can be sent to the server after acquisition. (Refer to...) Figures 7A-8B Provide its details.

[0062] Figure 6C This is a flowchart of an exemplary process for an exemplary safety post 210 according to an embodiment of this teaching. First, at 605, operating parameters for the safety post are set or specified, such as working parameters for generating a magnetic field and / or sensitivity levels for assessing the presence of metal or whether observed magnetic field changes correspond to a metal or electronic object used in the analysis of sensed signals. With the operating parameters set, at 615, one or more magnetic fields are generated based on the working parameters. During operation, sensing portions in different sections of the safety post obtain sensed information from, for example, a fluxgate sensor at 625. This sensed information is sent to a signal processing unit, which then analyzes the sensed information at 635 and determines the presence of a metal / electronic object based on signal processing at 645. If it is determined at 650 that no metal is detected (i.e., no metal / electronic object is detected), then the operation returns to step 625 for the next determination.

[0063] If a segment detects a metallic or electronic object at 650, then that segment activates its corresponding segment alarm at 655 to report the detection. Each segment sends its respective detection result (e.g., whether the detection is positive or negative) to the central controller 600, where the signal integration unit 610 integrates the detection results from different segments at 660. As discussed herein, in some embodiments, the central controller 600 may individually identify the presence of a metallic and / or electronic object at 665. In some embodiments, what is sent from each segment may be sensed information to the central controller 600 (instead of detection results—see the link between 645 and 660), thus completing the detection at the signal integration unit 610 based on sensed information from different segments. In some embodiments, what is sent from each segment to the central controller 600 may be a separate detection result (see the link between 650 and 660). In some embodiments, a segment may send both sensed information and detection results to the central controller for integrated processing.

[0064] For detected metallic / electronic objects, signal integration unit 610 controls the display of the detection result on touch-sensitive display screen 212 at 670. As discussed herein, in some embodiments, central controller 600 may send the detection result to server 640 via network 630 at 675. This option can be selected based on the application deploying security pillars. For example, the application may involve deploying different entry points of security pillars and a central control station to collect detection information from all deployed pillars. Specific applications involving such a setup may include corporate access control with multiple entry points at different entrances / exits, having a central monitoring facility to aggregate detection information from such entrances / exits.

[0065] In some embodiments, the detection of the presence of metal is based on the observed change in the magnetic field caused by the presence of an object containing metal. Different types of objects can have different metal contents. For example, metallic objects such as knives have a high metal content, while electronic objects can have a much lower metal content; for example, metal may only be present in limited areas within a smartphone (e.g., only in pins, transformers, PCBs, or chips). The different metal contents present in different types of objects can cause different changes in the magnetic field. The observed magnetic field changes caused by the presence of each type of object can be analyzed, quantitatively characterized, and then used to classify some subsequently observed magnetic field changes to see if similar types of objects caused the later observed magnetic field changes.

[0066] In some embodiments, different measurements are used to characterize changes in the magnetic field, such as the magnitude, phase, and intensity of the change. Figure 6DExemplary distributions 660 and 670 are illustrated, respectively, characterizing the changes in magnetic fields caused by the presence of metallic and electronic objects. In this illustration, the X-axis may represent the phase of the observed signal, the Y-axis may represent the frequency of the observed signal, and the Z-axis may represent the amplitude of the observed signal. In this illustration, the two exemplary distributions 660 and 670 are substantially different; one (e.g., 660) characterizes the distribution of observed magnetic field changes caused by the presence of metallic objects, and the other (e.g., 670) characterizes the distribution of observed magnetic field changes caused by the presence of electronic objects. Because the exemplary distributions 660 and 670 in the two illustrations are substantially different, they each provide a basis for modeling the characteristics of magnetic field changes caused by the presence of corresponding types of objects. In some embodiments, each of these exemplary distributions can be parameterized to enable future classification of object types (e.g., metallic or electronic objects) based on observed magnetic field changes. If a person passing through a safety post is neither carrying a metallic nor an electronic object, then the magnetic field change may not be observed, or at least at a negligible level, making it distinguishable from the distribution representing magnetic field changes caused by metallic objects or the distribution representing magnetic field changes caused by electronic objects.

[0067] Distributions corresponding to different object types can be used to generate models based on training data obtained from historical detections, for example, through machine learning. After quantitatively modeling distributions 660 and 670 through learning, appropriate criteria can be derived to classify future observations into any modeled class (i.e., metallic or electronic objects). Figure 6D The example shown illustrates that, for instance, a thresholding criterion derived from the feature space can be used to partition the two distributions 660 and 670, for example, to minimize the classification error rate. Such a criterion can be derived from, for example, a thresholding criterion derived from, the feature space. Figure 6E and Figure 6F The exemplary surface 680 shown is represented. Note that the exemplary thresholded surface 680 may appear linear. However, the criterion learned to serve as the dividing boundary between two exemplary models characterizing two exemplary distributions can be in any other form, such as a nonlinear surface. Furthermore, although Figures 6D-6F The exemplary distributions shown are in a three-dimensional feature space, but they are for illustrative purposes only and are not intended to be limiting. In general, features derived from sensor data related to magnetic field changes can be in a feature space of any dimension.

[0068] like Figures 6B-6C The system diagram and corresponding operating procedures depicted in the diagram support the detection of metallic or electronic objects by analyzing the characteristics or features of changes in the magnetic field. For example... Figure 6AAs shown, another alternative method for detecting electronic objects is via communication means, for example, by detecting signals from active electronic devices. Figure 7A An exemplary high-level architecture of a system implemented in a security column for detecting metallic / electronic objects, according to embodiments of this teaching, is depicted. The illustrated architecture includes different processing layers, including an Internet of Things (IoT) platform layer 700, a modeling layer 710, an information analysis layer 720, and an information collection layer 730.

[0069] The information gathering layer 730 includes means for receiving information from various sources to facilitate detection. This received information is then sent to different information analysis means at the information analysis layer 720 for signal processing and target object detection. In this illustrated architecture, depending on the detection results (implemented at the information analysis layer 720), the information gathering layer 730 can be further invoked to collect additional information, making the information flow between the information gathering layer 730 and the information analysis layer 720 bidirectional. When analyzing the information collected by the information gathering layer 730, the information analysis layer 720 can utilize models stored in the modeling layer 710 to facilitate its analysis. For example, the model can be trained on how to detect metallic and electronic objects based on the characteristics of magnetic field changes. The modeling layer 710 can include various training mechanisms configured to obtain appropriate models for different types of detection purposes by the information analysis layer 720 through training based on training data. In some embodiments, training data can be supplied to the modeling layer 710 via an IoT platform 700, which can be connected to many sources via a network connection.

[0070] As discussed herein, in addition to magnetic field information used to detect target objects, the information collection layer 730 can also collect other types of information, such as biometric information and ambient information. For example, this information can be acquired after a target object is detected to obtain information related to the target object. Figure 7BThe safety post, as illustrated in an embodiment of this teaching, can also collect and extract different types of information. As shown, the biometric / surrounding information that the safety post can request to acquire or extract includes facial information of a person with a detected metallic / electronic object, the person's body characteristics, ..., and some features related to the spatial environment. Additional features of the person and their surroundings can also be extracted from the acquired sensor information. For example, facial features that can be used, for example, to identify a person can be extracted. Facial features can also be used to estimate a person's emotional state (e.g., tension). Based on the acquired visual information, certain physical characteristics can also be estimated, including but not limited to a person's physiological characteristics (e.g., height, hair color, build, jacket color, etc.), estimated behaviors (e.g., waving, shouting, limb movements, etc.), and movements (e.g., how fast a person walks). Surrounding information can also be acquired from the scene where the target object is detected and then used to estimate certain spatial parameters associated with the person, such as the person's spatial location / position and / or the distance between the person and a reference point in space.

[0071] To aid in the extraction and estimation of various features as discussed in this paper, different models can be trained at modeling layer 710. Figure 7C Different types of models according to embodiments of this teaching are illustrated, which the safety column can use to detect different types of information. As discussed herein, modeling layer 710 can utilize training data collected at IoT layer 700 to train models for different purposes. For example, the detection of metallic and / or electronic objects can be performed based on a model trained on training data from previously confirmed detections. Models for detecting metallic objects can be derived such that they provide guidance for subsequent detections. Similarly, models for detecting electronic objects can also be trained based on past ground-based training data that provides information about expected characteristics associated with magnetic field changes observed from electronic objects. Such expected characteristics of magnetic field changes in electronic objects can be distinguished from those of magnetic field changes in metallic objects. Such distinctions can also be embedded in corresponding models learned for each type of such target object.

[0072] Furthermore, as discussed herein, additional information can be analyzed in conjunction with each detection of the target object. For example, once a target object (or a metallic or electronic object) is detected, biometric, behavioral, physical, or spatial information about the surrounding environment can be acquired, providing further information for each detection. To achieve this, models can be trained to derive such additional information. For example, models for facial recognition, for estimating human behavior, and for estimating spatial features associated with a person can also be trained and used. Models for estimating facial features can include facial color detection models for detecting color patches corresponding to faces in an image and / or facial surface models using depth information associated with a face. Similarly, models for estimating human behavior can be trained to estimate human body characteristics (such as height or waving of a person or hand) and / or certain human behaviors (such as anger). Models for estimating motion parameters associated with a person can also be trained. In some embodiments, models can also be obtained via training for determining the distance and / or specific location of a person, such as... Figure 7C As shown in the image.

[0073] like Figure 7A The information analysis layer 720 shown may include various modules that can control the information collection layer 730 to obtain the required information and process the signals from the information collection layer 730 based on the model provided by the modeling layer 710. In some embodiments, the information analysis layer 720 may include signal processing units in different segments and a signal integration unit 610 (see [link to documentation]). Figure 6B This can be integrated or generally organized as a target object and surrounding information detection module. As discussed herein, electronic objects (such as smartphones or tablets) can be distinguished from metallic objects by detecting different patterns of magnetic field changes caused by the amount of metal in the object. When the electronic object is active (i.e., turned on), it can alternatively be detected via communication means. In some embodiments, two different methods for detecting electronic objects can be used in different operating modes, e.g., together or separately. For example, based on the analysis of magnetic field changes, an initial estimate of whether an electronic object has been detected can be derived, which can then be confirmed using communication means. As another example, metallic objects can be detected based on the analysis of sensed magnetic field changes, while electronic objects can be detected separately using communication means.

[0074] Figure 8AAn exemplary high-level diagram depicts a module 800 in a safety column for detecting target objects and surrounding information according to an embodiment of this teaching. In this illustrated embodiment, the target object and surrounding information detection module 800 includes multiple units for detecting metallic / electronic objects, including a metal object detector 805, an electronic object detector 810, a communication unit 820, and a communication response signal detector 830. In some embodiments, in operation, when a signal is received from a sensing component (e.g., a fluxgate sensor), the metal object detector 805 analyzes the signal to detect changes in the magnetic signal. Detection may be based on one or more models for detecting metallic objects stored in a model storage device 806. As discussed herein, the models for detecting metallic objects can be generated based on machine learning from training data representing, for example, changes in the magnetic field caused by the presence of a metallic object. If a metallic object is detected, the metal object detector 805 sends a signal indicating the presence of the metallic object.

[0075] The electronic object detector 810 can also continue to detect the presence of electronic objects. In some embodiments, it can operate even when no metal object is detected and the metal object detector 805 notifies it. In some embodiments, the electronic object detector 810 can also receive sensed magnetic signals from a magnetic flux sensor and analyze magnetic field changes to detect the presence of electronic objects. For example, magnetic field changes caused by electronic objects may have characteristics different from those caused by metal objects or the absence of both metal and electronic objects. Detection can be based on one or more models for detecting electronic objects stored in the model storage device 806. As discussed herein, the models for detecting electronic objects can be generated based on machine learning from training data representing, for example, magnetic field changes caused by the presence of electronic objects. In some embodiments, the distribution of magnetic field changes due to the presence of electronic objects can be captured in the model. In some embodiments, the difference between the distribution of magnetic field changes for electronic objects and the distribution of magnetic field changes for metal objects can also be captured in the models for detecting both metal and electronic objects.

[0076] The detection of an electronic object via magnetic field change analysis can be further confirmed using communication means. In some embodiments, the detection of an active electronic object can rely directly on communication means without the need for magnetic field change analysis. To detect an active electronic object via communication means, the electronic object detector 810 invokes the communication unit 820 to send a communication signal within a predetermined scope or range according to one or more communication protocols stored in the communication protocol configuration storage device 802. As discussed herein, the communication protocol can be any communication framework and its corresponding protocol, including but not limited to WiFi, Bluetooth, etc. Adhering to the protocols of different wireless communication frameworks, the communication unit 820 sends out the communication signal and then notifies the communication response signal detector 830 to wait to see if a response signal is received. If the communication response signal detector 830 receives a response signal, then the electronic object is present and the electronic object detector 810 sends a signal indicating that the electronic object has been detected.

[0077] As discussed herein, in some embodiments, additional information can be acquired that can help reveal more about the scene associated with the detection of a metal or electronic object. This additional information includes biometric information of the person associated with the detected target object, and behavioral / physical / spatial information observed in the scene. To achieve this, the target object and surrounding information detection unit 800 also includes, for example, a biometric information detector 840, a surrounding information detector 860, a behavioral information detector 850, and an emotion detector 870. In some embodiments, after detecting a metal or electronic object, the biometric information detector 840 can be invoked to acquire biometric information of the person carrying the detected metal or electronic object. This biometric information may include facial information or any information related to the person's body.

[0078] In some embodiments, depending on application needs, other modules for detecting other types of information can also be invoked to collect other types of information. For example, an ambient information detector 860 (not shown) can be activated to collect and analyze information about the surrounding scene and generate useful information. Furthermore, the carrier's emotions and / or behaviors can also be informative, thus the behavior information detector 850 and / or emotion detector 870 can also be invoked to collect information for analysis. To support such activities, each activated module activates relevant sensors in the cluster of multimodal sensors 804 and collects the required information from the environment. Multimodal sensors can include, but are not limited to, visual sensors, acoustic sensors, depth sensors, or any other type of sensor.

[0079] Based on the acquired sensor information, each invoked module can act on relevant information and extract or identify informative features. For example, the biometric information detector 840 can collect, for example, visual facial information and extract relevant features characterizing a person's face. The ambient information detector 860 can collect visual images of the environment in which the person is located and estimate various information related to the environment or its spatial characteristics, such as the estimated location of the person or the distance to the camera that captured the image. The behavior information detector 850 can collect sensor data to facilitate its analysis of human behavior. Human behavior can be observed visually (e.g., clenching a fist) and auditorily (e.g., shouting) and estimated based on sensor information from different modalities. The emotion detector 870 can also be applied to analyze, for example, human facial expressions to detect certain types of emotions, such as anger, anxiety, fear, etc. This information about the person and their surroundings derived from multimodal sensor data can be based on various models stored in 806. To send this exported information to a display screen or server, different types of information obtained by various detectors (840, 850, 860, and 870) can then be sent to the carrier packet generator 880, where all information will be organized and then sent out for display on screen 620 or to server 650 (see [link to relevant documentation]). Figure 6B ).

[0080] Figure 8B This is a flowchart illustrating an exemplary process of a target object and surrounding information detection module 800 according to an embodiment of this teaching. In operation, at 812, a change in magnetic field sensed by, for example, a fluxgate sensor is first received. At 815, this received information is processed to detect the presence of a metallic object. If it is determined at 817 that no metal is detected, then the processing proceeds to 822 to further detect the presence of an electronic object. If it is determined at 817 that a metallic object is detected, then the signal processing unit triggers a section alarm to report the detection by sending a signal indicating the detection of a metallic object at 825, and then proceeds to 822 to detect the presence of an electronic object.

[0081] In some cases, it is possible for electronic and metallic objects to coexist. When detecting both, the threshold for determining whether any metal is detected can be set quite low (because electronic objects can contain a relatively small amount of metal). If the detected metal exceeds the threshold, then the determination of both the metal and electronic objects is performed. In this case, the process continues to detect electronic objects even after a metal object has been detected. As discussed in this paper, due to the relatively low metal content in electronic objects, the reliability of detecting their presence can be enhanced through other means.

[0082] When an electronic object is detected at position 826 based on a change in the magnetic field, the process can optionally continue using communication methods to confirm or enhance the detection of the activated electronic object. To detect an activated electronic object via communication methods, Figure 8A The communication unit 820 sends one or more communication signals at 827 according to some communication protocol within a predetermined range and parameters, triggering the communication response signal detector 830 to detect any response signal from the electronic object. If it is determined at 829 that no response signal is received, it indicates that no active electronic object has been detected. In this case, the process proceeds to step 812 for the next detection. If a response signal is received, it indicates that an active electronic device has been detected. In this case, the communication response signal detector 830 notifies the electronic object detector 810, which sends a signal to the safety post at 832 to report the detection of the electronic object.

[0083] As discussed herein, after the detection of a metallic / electronic object, additional information associated with the detection can be acquired, analyzed, and reported. If it is determined at 835 that additional information should not be acquired, the process proceeds to step 812 for the next detection. If additional information is to be acquired, then the multimodal sensor 804 is activated to acquire, for example, biometric and environmental information at 837. Some of this acquired information (such as biometric information of the person carrying the detected target object) can be sent at 842 via network 640 to, for example, server 650 for archiving evidence of the detection event. If it is determined at 845 that additional information should be used to extract other relevant features in the surrounding environment that more comprehensively characterize the person carrying the detected target object, then various modules (e.g., 840, 850, 860, and / or 870) can be invoked to detect different features associated with the person and the surrounding environment at 837. This includes, but is not limited to, facial features, spatial features (distance, location, etc.), emotion-related assessments, behavioral-related assessments, etc. Once such features are extracted, they can be sent at 852 to, for example, server 650, for archiving surrounding evidence associated with the detection.

[0084] Figure 9This is an illustrative diagram of an exemplary mobile device architecture that can be used to implement a dedicated system for carrying out the present teachings, according to various embodiments. In this example, the device on which the present teachings are implemented corresponds to mobile device 900, which includes, but is not limited to, smartphones, tablets, music players, handheld game consoles, GPS receivers, and wearable computing devices (e.g., glasses, watches, etc.), or any other form factor. Mobile device 900 may include one or more central processing units (“CPU”) 940, one or more graphics processing units (“GPU”) 930, a display 920, memory 960, a communication platform 910 (such as a wireless communication module), a storage device 990, and one or more input / output (I / O) devices 940. Any other suitable components (including, but not limited to, a system bus or controller (not shown)) may also be included in mobile device 900. Figure 9 As shown, a mobile operating system 970 (e.g., iOS, Android, Windows Phone, etc.) and one or more applications 980 can be loaded from storage device 990 into memory 960 for execution by CPU 940. Application 980 may include a browser or any other suitable mobile application for managing the session system on mobile device 900. User interaction can be implemented via I / O device 940 and provided to the automated dialogue partner via network(s)120.

[0085] To implement the various modules, units, and functions described herein, a computer hardware platform can be used as the hardware platform for one or more of the elements described herein. The hardware components, operating systems, and programming languages ​​of such computers are conventional in nature, and it is assumed that those skilled in the art are sufficiently familiar with them to adapt these technologies to the appropriate setups described herein. A computer with user interface components can be used to implement a personal computer (PC) or other type of workstation or terminal device, but if properly programmed, the computer can also act as a server. It is believed that those skilled in the art are familiar with the structure, programming, and general operation of such computer equipment; therefore, the accompanying drawings should be self-evident.

[0086] Figure 10This is an illustrative diagram of an exemplary computing device architecture that can be used to implement a dedicated system embodying the present teachings, according to various embodiments. Such a dedicated system incorporating the present teachings has a functional block diagram illustrating a hardware platform including user interface elements. The computer can be a general-purpose computer or a dedicated computer. Both can be used to implement a dedicated system embodying the present teachings. As described herein, this computer 1000 can be used to implement any component of a conversation or dialogue management system. For example, a conversation management system can be implemented on a computer such as computer 1000 via its hardware, software programs, firmware, or a combination thereof. Although only one such computer is shown for convenience, the computer functions associated with the conversation management system as described herein can be implemented in a distributed manner on multiple similar platforms to distribute the processing load.

[0087] Computer 1000 includes, for example, a COM port 1050 connected to or from a network to facilitate data communication. Computer 1000 also includes a central processing unit (CPU) 1020 in the form of one or more processors for executing program instructions. This exemplary computer platform includes an internal communication bus 1010, various forms of program storage devices and data storage devices (e.g., disk 1070, read-only memory (ROM) 1030, or random access memory (RAM) 1040) for various data files to be processed and / or transferred by computer 1000, and program instructions that may be executed by CPU 1020. Computer 1000 also includes I / O components 1060 to support input / output flows between the computer and other components therein, such as user interface elements 1080. Computer 1000 can also receive programming and data via network communication.

[0088] Therefore, aspects of the methods for dialogue management and / or other processes described above can be implemented in programming. The programmatic aspects of a technology can be viewed as a “product” or “artifact,” typically in the form of executable code and / or associated data executed on or implemented in some type of machine-readable medium. Tangible, non-transitory “storage” media include any or all memory or other storage devices (such as various semiconductor memories, tape drives, disk drives, etc.) used in computers, processors, etc., or their associated modules, which can provide storage for software programming at any time.

[0089] Sometimes, all or part of software can be transmitted via networks such as the Internet or various other telecommunications networks. For example, such communication, combined with session management, can enable the loading of software from one computer or processor into another. Therefore, another type of medium that can carry software elements includes optical, electrical, and electromagnetic waves, such as those used via wired and optical landline networks and physical interfaces between local devices via various air links. Physical elements carrying such waves (such as wired or wireless links, optical links, etc.) can also be considered as media carrying software. As used herein, unless limited to tangible “storage” media, terms such as “readable medium” for a computer or machine refer to any medium involved in providing instructions to a processor for execution.

[0090] Therefore, machine-readable media can take many forms, including but not limited to tangible storage media, carrier media, or physical transmission media. Non-volatile storage media include, for example, optical discs or disks, any storage device such as one or more in any computer, which can be used to implement the system shown or any component thereof. Volatile storage media include dynamic memory, such as the main memory of such a computer platform. Tangible transmission media include coaxial cables; copper wires and optical fibers, including wires that form a bus within a computer system. Carrier transmission media can take the form of electrical or electromagnetic signals or sound waves or light waves (such as those generated during radio frequency (RF) and infrared (IR) data communications). Therefore, common forms of computer-readable media include, for example: floppy disks, flexible disks, hard disks, magnetic tapes, any other magnetic media, CD-ROMs, DVDs or DVD-ROMs, any other optical media, punched cardboard tapes, any other physical storage media with a perforated pattern, RAM, PROMs and EPROMs, FLASH-EPROMs, any other memory chips or cassettes, carriers for transporting data or instructions, cables or links for transporting such carriers, or any other media from which a computer can read programming code and / or data. Many of these forms of computer-readable media may involve carrying one or more sequences of one or more instructions to a physical processor for execution.

[0091] Those skilled in the art will recognize that this teaching is capable of various modifications and / or enhancements. For example, while the implementations of the various components described above can be carried out in hardware devices, they can also be implemented as pure software solutions—e.g., installations on existing servers. Furthermore, the fraudulent network detection techniques disclosed herein can be implemented as firmware, firmware / software combinations, firmware / hardware combinations, or hardware / firmware / software combinations.

[0092] While the foregoing has described what is considered to constitute this teaching and / or other examples, it should be understood that various modifications can be made thereto, and the subject matter disclosed herein can be implemented in various forms and examples, and the teachings can be applied to many applications, only some of which are described herein. The following claims are intended to claim protection for any and all applications, modifications, and variations that fall within the true scope of this teaching.

Claims

1. A method for detecting an electronic target object, the method being implemented on at least one machine including at least one processor and a communication platform capable of connecting to a network, the method comprising: Generate a magnetic field; Sensing magnetic field changes associated with the presence of objects near the magnetic field; Extract features characterizing changes in the magnetic field; The presence of a mixture of metals and other substances is detected based on one or more models characterizing the expected magnetic field changes caused by the presence of the object, based on extracted features and magnetic field changes that satisfy specific criteria in the feature space. Based on the presence of the mixture of the metal and other substances, the object is determined to be an electronic target object; as well as If an electronic target object is detected, an alarm is triggered in response to the detection.

2. The method as described in claim 1, wherein, The electronic target object is either turned on or off.

3. The method as described in claim 1, wherein, The features include at least one of phase, frequency, and amplitude associated with the change in magnetic field.

4. The method of claim 2, further comprising determining whether the electronic target object is turned on.

5. The method of claim 4, wherein, The specific steps include: Transmit at least one wireless signal according to at least one corresponding communication protocol; Receive a response signal from an electronic target object in response to any one of the at least one wireless signals; If a response signal is received, the electronic target object is considered to be activated.

6. The method of claim 1, further comprising collecting additional information and / or surrounding information related to the person carrying the target object when the target object is detected.

7. A machine-readable medium having information recorded thereon for detecting electronic target objects, the information causing the machine to perform the following actions when read by the machine: Generate a magnetic field; Sensing magnetic field changes associated with the presence of objects near the magnetic field; Extract features characterizing changes in the magnetic field; The presence of a mixture of metals and other substances is detected based on one or more models characterizing the expected magnetic field changes caused by the presence of the object, based on extracted features and magnetic field changes that satisfy specific criteria in the feature space. Based on the presence of the mixture of the metal and other substances, the object is determined to be an electronic target object; as well as If an electronic target object is detected, an alarm is triggered in response to the detection.

8. The medium as claimed in claim 7, wherein, The electronic target object is either turned on or off.

9. The medium as claimed in claim 7, wherein, The features include at least one of phase, frequency, and amplitude associated with the change in magnetic field.

10. The medium as claimed in claim 8, wherein, When the information is read by the machine, it enables the machine to further execute actions to determine whether the electronic target object is turned on.

11. The medium as claimed in claim 10, wherein, The specific steps include: Transmit at least one wireless signal according to at least one corresponding communication protocol; Receive a response signal from an electronic target object in response to any one of the at least one wireless signals; If a response signal is received, the electronic target object is considered to be activated.

12. The medium as claimed in claim 7, wherein, When the information is read by the machine, it enables the machine to further perform actions such as collecting additional information and / or surrounding information related to the person carrying the target object if the target object is detected.

13. An apparatus for detecting an electronic target object, comprising: A magnetic field generating unit, the magnetic field generating unit being configured to generate a magnetic field; One or more sensors, the one or more sensors being configured to sense changes in the magnetic field associated with the presence of an object near the magnetic field; Signal processing unit, the signal processing unit being configured for Extracting features characterizing changes in the magnetic field. The presence of a mixture of metals and other substances is detected based on one or more models characterizing the expected magnetic field changes caused by the presence of the object, based on extracted features and magnetic field changes that satisfy specific criteria in the feature space. as well as Based on the presence of the mixture of the metal and other substances, the object is determined to be an electronic target object; as well as An alarm triggering unit is configured to trigger an alarm in response to the detection of an electronic target object.

14. The apparatus of claim 13, wherein, The electronic target object is either turned on or off.

15. The apparatus of claim 13, wherein, The features include at least one of phase, frequency, and amplitude associated with the change in magnetic field.

16. The apparatus of claim 14, further comprising a communication unit configured to determine whether an electronic target object is activated by transmitting at least one wireless signal according to a corresponding communication protocol.

17. The apparatus of claim 16, further comprising a communication response signal detector configured to receive a response signal transmitted from an electronic target object in response to any one of the at least one wireless signal to identify that the electronic target object is turned on.

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