National gate safety science popularization intelligent interaction system for detecting harmful substances of imported commodities

Abstract

The invention relates to a national security science popularization intelligent interaction system for detecting harmful substances in imported commodities, and relates to the technical field of man-machine interaction and information visualization, and the system comprises a multi-mode substance sampling probe, a spectral data materialization matrix and a central processing system. The probe is used for collecting identification and postures and providing tactile feedback; the materialization matrix presents the scientific data set in a touchable three-dimensional physical form; and the central processing system calculates the position of the vernier according to the probe attitude, extracts the amplitude and gradient characteristics of the position, generates a corresponding touch instruction and sends the touch instruction to the probe. According to the method, a visual navigation and tactile feedback closed loop is constructed, abstract data is converted into observable, touchable and sensible immersive experience, and the problems that in the prior art, data presentation is single, interaction is not visual, and feature perception is lacked are solved. A user can explore data in a natural posture and visually perceive the texture of the data through physical vibration, and the vividness and effectiveness of scientific popularization are remarkably improved.

Description

Technical Field

[0001] This application relates to the fields of human-computer interaction and information visualization technology, and in particular to a smart interactive system for border security science popularization related to the detection of hazardous substances in imported goods. Background Technology

[0002] With the increasing frequency of global trade, the importance of national border biosecurity and commodity quality safety has become increasingly prominent. Customs and other regulatory departments utilize various scientific testing methods, such as spectral analysis and chromatographic analysis, in the inspection of import and export commodities to identify and quantify the biological information of potentially harmful chemicals, illegal additives, or invasive alien species. These testing processes generate a large amount of highly specialized and complex scientific datasets.

[0003] How to present these abstract and unstructured scientific test data to the general public without a professional background in an accurate, vivid, and easy-to-understand way is an important challenge facing science popularization work in the field of national border security.

[0004] Currently, popular science presentations of this type of scientific data typically employ methods such as graphic panels, video animations, or two-dimensional / three-dimensional models based on computer screens. However, these methods essentially present abstract data in a purely visual form, confining the data itself to a two-dimensional plane or virtual three-dimensional space, creating a significant perceptual barrier between the data and the audience. Viewers can only act as passive observers, finding it difficult to develop an immersive and embodied understanding of the data's fluctuations, changes, and distribution patterns. This significantly weakens the appeal and retention of the popular science content.

[0005] Furthermore, when it comes to exploratory data analysis, existing technologies typically rely on mouse, keyboard, or touchscreen interaction methods. Users pan, zoom, or rotate data models by clicking, dragging, and other actions, which is an indirect and unnatural mode of interaction. There is a significant cognitive disconnect between user actions and the intuitive behaviors of exploring a physical entity in the real world (e.g., moving one's viewpoint, touching to perceive), which not only increases the complexity of the operation but also undermines the coherence and immersion of the exploration process.

[0006] More importantly, traditional visualization methods struggle to convey the deep, intrinsic characteristics of data. For instance, in a set of spectral data, a high, narrow absorption peak and a gentle, broad peak represent drastically different physicochemical meanings. The former might indicate a high concentration and significant characteristic of a substance, while the latter could represent background noise or the superposition of signals from multiple substances. In purely visual displays, users may see the morphological differences, but it's difficult to intuitively quantify and perceive these differences in "sharpness" or "steepness." Current technology lacks a mechanism that can transform key features such as local gradients and amplitudes of data into a tangible physical feedback in real time and synchronously, preventing users from "touching" the "texture" of the data and thus missing out on a deeper understanding.

[0007] Therefore, there is an urgent need to propose a brand-new technical solution to overcome the shortcomings of existing technologies, such as the single data presentation method, unintuitive interactive experience, and lack of perception of key features. Summary of the Invention

[0008] The purpose of this application is to provide a smart interactive system for border security science popularization for the detection of hazardous substances in imported goods. This system solves the problems in existing science popularization interactive technology solutions, such as the weak correlation between interactive operation and scientific detection principles, and the fact that detection data is mostly presented in the form of abstract two-dimensional charts, making it difficult for users to intuitively understand the inherent characteristics and changing patterns of the data.

[0009] To address the aforementioned technical problems, this invention provides a new technical solution.

[0010] Firstly, this application provides a smart interactive system for border security education on the detection of hazardous substances in imported goods. This system includes:

[0011] The input signal processing module is configured to receive an input signal related to the model of the physical commodity under test, generated by a multimodal material sampling probe.

[0012] The data retrieval and mapping module is configured to retrieve a scientific testing dataset from the database based on the input signal, and control the spectral data materialization matrix to present the scientific testing dataset as a three-dimensional physical form.

[0013] The navigation control module is configured to track the real-time attitude of the multimodal material sampling probe in order to control the data cursor to navigate on the three-dimensional physical shape.

[0014] The tactile feedback generation module is configured to generate a tactile feedback signal based on local data features of the current position of the data cursor, and send the tactile feedback signal to the multimodal material sampling probe for presentation.

[0015] In one embodiment, the multimodal material sampling probe includes a near-field communication reader, an inertial measurement unit, and a tactile feedback unit. The near-field communication reader is used to identify the model of the object under test to generate its unique identifier. The inertial measurement unit is used to acquire the initial and real-time attitude of the multimodal material sampling probe. The tactile feedback unit is used to generate physical vibrations based on the tactile feedback signals.

[0016] In one embodiment, the spectral data materialization matrix comprises a physical array consisting of multiple independently controllable luminescent units. The data retrieval and mapping module controls the physical height and / or emission color of each luminescent unit, and all luminescent units together constitute the three-dimensional physical form.

[0017] In one embodiment, the input signal is a composite input signal that includes the unique identifier generated by the near-field communication reader and a sampling point identifier corresponding to a specific region on the model of the physical object under test, identified by the photoelectric sensor on the multimodal material sampling probe.

[0018] In one embodiment, the navigation control module is configured to determine the position of the data cursor on the three-dimensional physical shape by calculating the change in the real-time attitude of the multimodal material sampling probe relative to the initial attitude. The position of the data cursor... The roll angle of the multimodal material sampling probe and pitch angle The decision, and its calculation method, includes:

[0019] ;

[0020] in, For time, for The position of the data cursor at any given time. and Its coordinate components, and They are respectively The roll and pitch angles at any given moment. This is the initial position of the cursor. and This is the preset attitude sensitivity coefficient. and The size boundary of the materialization matrix of the spectral data. Let be a constraint function, when the variable exist Return when within the interval ,when Time return ,when Time return .

[0021] In one embodiment, the local data feature includes an amplitude feature. and gradient features The amplitude feature Corresponding to the data cursor in The height of the three-dimensional physical form at the current position. The gradient feature. Corresponding to the three-dimensional physical form in the data cursor at The rate of change of the local space at the current position at any given time.

[0022] In one embodiment, the tactile feedback signal generated by the tactile feedback generation module instantaneous amplitude From the amplitude characteristics Modulation, its instantaneous frequency From the gradient features Modulation, the generation methods of which include:

[0023] ;

[0024] in, For time, for tactile feedback signals at all times and They are respectively Instantaneous amplitude and instantaneous frequency at time 1 / 2. and They are respectively Amplitude and gradient characteristics at time intervals, and The preset tactile gain coefficient, and These are the preset base amplitude and base frequency, respectively.

[0025] Secondly, this application provides a smart interactive method for border security education on the detection of hazardous substances in imported goods, which includes the following steps:

[0026] A multimodal material sampling probe is used to interact with the physical product model to generate an input signal;

[0027] The system receives the input signal, retrieves the scientific testing dataset corresponding to the model of the entity to be tested, and controls the spectral data materialization matrix to present the scientific testing dataset as a three-dimensional physical form.

[0028] Establish a data resonance feedback closed loop, in which:

[0029] The real-time attitude of the multimodal material sampling probe is tracked to control the data cursor to navigate on the three-dimensional physical shape;

[0030] Based on the local data features of the current position of the data cursor, a tactile feedback signal is generated;

[0031] The tactile feedback signal is transmitted to the multimodal material sampling probe for presentation.

[0032] In summary, this application includes at least one of the following beneficial technical effects:

[0033] 1. This invention, by setting a materialized matrix for spectral data and mapping scientific testing datasets to the height and / or color of controllable luminescent units within this matrix, achieves the transformation of abstract one-dimensional or two-dimensional digital information into a directly observable three-dimensional physical form. This setup allows users to visually perceive the overall outline, characteristic peak positions, and relative intensities of the data from multiple physical perspectives, providing a more direct physical representation of the data structure compared to two-dimensional charts presented on a flat panel display.

[0034] 2. This invention, by setting up a navigation control module, correlates the real-time attitude changes of the user-held multimodal material sampling probe with the position of the data cursor on the three-dimensional physical form. This setting enables users to actively and precisely control the movement of their focus point in the data space, transforming the passive viewing of preset results into an active and exploratory interaction with data details. Users can independently select and focus on the data areas of interest for in-depth observation.

[0035] 3. This invention establishes a data resonance feedback closed loop, which correlates the local data features of the current position of the data cursor with the physical properties of the tactile feedback signal in real time. Visual and tactile information are presented collaboratively, allowing users to simultaneously perceive the specific numerical value and degree of change of the data at a local level through tactile sensation while visually observing the data pattern. This provides direct physical feedback for users to understand abstract data features. Attached Figure Description

[0036] Figure 1 This is the system architecture diagram of this application;

[0037] Figure 2 This is a schematic diagram of the multimodal material sampling probe structure of this application;

[0038] Figure 3 This is a schematic diagram of the physical matrix structure of the spectral data in this application;

[0039] Figure 4 This is a flowchart of the method used in this application;

[0040] Explanation of reference numerals in the attached diagram: 10, Input signal processing module; 20, Data retrieval and mapping module; 30, Navigation control module; 40, Tactile feedback generation module. Detailed Implementation

[0041] The following is in conjunction with the appendix Figure 1 -Appendix Figure 4 This application will be described in further detail below.

[0042] Example: See attached document Figure 1 This embodiment discloses a smart interactive system for border security education on the detection of hazardous substances in imported goods, including:

[0043] The input signal processing module 10 is configured to receive an input signal related to the model of the physical commodity under test, generated by a multimodal material sampling probe.

[0044] The input signal processing module 10 is configured to receive data packets transmitted wirelessly by the multimodal material sampling probe. In one specific embodiment, the data packet employs a predefined structured format, such as a data structure containing multiple key-value pairs. This data structure may include: a sample identifier field, a sampling point identifier field, an initial pose field, and a timestamp field.

[0045] The sample identifier field stores a unique identifier read from the near-field communication tag on the physical product model under test. This identifier can be a string of alphanumeric characters of a specific length or a universally unique identifier. The sampling point identifier field stores encoded information identified by the photoelectric sensor on the multimodal material sampling probe and associated with a specific physical area on the physical product model under test. This encoded information can be a specific RGB color value or a preset integer code.

[0046] The initial attitude field stores the attitude data collected by the inertial measurement unit inside the multimodal material sampling probe at the moment of its first contact with the test object model. To accurately describe spatial orientation and avoid gimbal lock issues, this attitude data is expressed in unit quaternions. Stored in the form of, where Let be the four components of a quaternion, and satisfy . .

[0047] Reference Appendix Figure 2 The multimodal material sampling probe is a stand-alone, handheld physical device. Its casing can be made of engineering plastic or metal, and its shape is designed as a rod or pen for easy gripping and precise operation. The probe tip has an interactive end for physical contact or close-range interaction with a specific area on the physical product model being tested.

[0048] Inside the housing is an integrated near-field communication (NFC) reader. The antenna portion of this reader can be positioned near the interaction point, operating at a frequency of 13.56 MHz, conforming to ISO / IEC 14443 or ISO / IEC 15693 standards. When the interaction point is brought close to the NFC tag attached to the physical product model under test, the reader is configured to read the unique identifier stored within the tag.

[0049] An inertial measurement unit (IMU) is also integrated inside the housing. In one embodiment, this IMU is a six-axis sensor integrating a three-axis accelerometer and a three-axis gyroscope. This unit is configured to continuously acquire three-dimensional spatial attitude data of the probe at a preset sampling frequency. The acquired raw data is processed by an internal data fusion algorithm, and the output is a unit quaternion representing its real-time spatial attitude. .

[0050] An integrated photoelectric sensor is also located inside the housing, with its photosensitive surface facing the same direction as the interactive terminal. In one embodiment, the photoelectric sensor is a color sensor configured to identify a specific color code of the sampling point area when the interactive terminal touches or approaches a sampling point on the physical product model to be tested, and convert the color code into a predefined sampling point identifier.

[0051] The housing also integrates a haptic feedback unit. In one embodiment, this unit is a linear resonant actuator or a piezoelectric ceramic actuator. The unit is configured to receive control commands sent by a central processing system and, based on the instantaneous amplitude in the commands... and instantaneous frequency The parameters generate corresponding physical vibrations.

[0052] In addition, the probe includes an internal microcontroller and a wireless communication module (e.g., a Bluetooth Low Energy module). The microcontroller connects to the near-field communication reader, inertial measurement unit, and photoelectric sensors via a serial bus (e.g., I2C or SPI). It is responsible for coordinating data acquisition from the sensors, packaging the acquired unique identifiers, sampling point identifiers, and attitude quaternions into structured data frames, and sending them to the central processing system via the wireless communication module. Simultaneously, it is also responsible for receiving haptic control commands from the central processing system and driving the haptic feedback unit.

[0053] After receiving the data packet, the input signal processing module 10 first parses and verifies it.

[0054] The verification process may include: checking if the sample identifier exists in a preset list of valid sample identifiers; verifying whether the sampling point identifier is a valid sampling point associated with that sample identifier; and confirming whether the quaternion norm in the initial attitude field is within a preset error threshold (e.g., the absolute value of the difference from 1 is less than 10). -5 This is to ensure the validity and integrity of the data.

[0055] After successful verification, the input signal processing module 10 distributes the parsed data. Specifically, it transmits the sample identifier and sampling point identifier to the data retrieval and mapping module 20 as the basis for data retrieval. Simultaneously, it processes the initial attitude quaternions. It is transmitted to the navigation control module 30 and used as a reference for subsequent navigation control.

[0056] The data retrieval and mapping module 20 is configured to retrieve scientific test datasets from the database based on the input signal and control the spectral data materialization matrix to present the scientific test datasets as a three-dimensional physical form.

[0057] After receiving the sample identifier and sampling point identifier from the input signal processing module 10, the data retrieval and mapping module 20 uses these two identifiers as a composite primary key to perform a retrieval operation in a pre-set database system. This database system stores multiple scientific testing datasets, each associated with a specific set of sample identifiers and sampling point identifiers. The retrieval operation returns a one-dimensional scientific testing dataset that precisely matches the input identifier. This dataset It is a collection An array of numerical values ​​for data points can be represented as: , where each element It represents the signal intensity value under a specific independent variable (e.g., wavelength in spectral analysis or retention time in chromatographic analysis).

[0058] The dataset was successfully retrieved. Then, the data retrieval and mapping module 20 executes the data mapping process, transforming the one-dimensional dataset... This is converted into a set of two-dimensional instructions for controlling the materialization matrix of spectral data. This instruction set defines the dimensions of each element in the spectral data materialization matrix. The physical state of the light-emitting unit. This process includes height mapping and color mapping.

[0059] Each size is The physical state of the light-emitting units. This process includes height mapping and color mapping. In height mapping, the module first calculates the dataset. The maximum value in and minimum value Subsequently, for each luminescent unit in the spectral data materialization matrix, its coordinates... target height It is calculated through linear normalization. This calculation converts the data points... The value is mapped to the physical height range of the spectral data materialization matrix. Inside. Its calculation formula is:

[0060] ;

[0061] This formula applies to all rows. , so that in the same column All the light-emitting units on the surface have the same height, thus unfolding the one-dimensional data sequence along one axis to form a three-dimensional physical form.

[0062] In color mapping, the module determines the target color for each emitting unit. In one embodiment, the color is determined by its corresponding normalized height value. The module can use a preset color lookup table. This lookup table maps an input value in the range [0,1] to a specific color value. The module first calculates the normalized height of each emitting unit. Then use Used as an index or input, the corresponding color is retrieved from the color lookup table. The lookup table can be configured to map lower height values ​​to cool tones and height values ​​above a certain threshold to warm tones, in order to visually distinguish different ranges of data.

[0063] Reference Appendix Figure 3 The spectral data materialization matrix is ​​a physical display device, whose basic structure includes a base, a matrix controller mounted on the base, and a [missing information - likely a component or component]. An array of independently controllable light-emitting units. The matrix controller is connected to the central processing system via a wired interface (e.g., USB or Ethernet interface) to receive and parse control commands sent by the data retrieval and mapping module 20.

[0064] In one specific embodiment, each light-emitting unit includes a linear actuator and a light source mounted on top of the actuator. The linear actuator can be a miniature servo motor or a stepper motor, and its function is to change its extension length according to a control signal, thereby changing the physical height of the light source in the Z-axis direction perpendicular to the base.

[0065] The light source can be an independently addressable full-color LED. This type of LED integrates a driver chip, allowing the brightness values ​​of its red, green, and blue channels to be set individually via serial data signals, thereby mixing specific colors.

[0066] The matrix controller internally contains a microprocessor or field-programmable gate array (FPGA). Upon receiving an instruction set from the central processing system containing the target height and target color of all light-emitting units, the controller executes the instruction distribution task. For height control, the controller generates a specific pulse-width modulation (PWM) signal for each linear actuator, the duty cycle of which is proportional to the target height value, thereby driving the actuator to move to the specified height position. For color control, the controller encodes the target RGB color values ​​into a serial data stream using a specific protocol and sends this data stream to multiple light sources connected in series to achieve precise color setting for all light sources.

[0067] Through the aforementioned structure, the spectral data materialization matrix can transform a digitized scientific dataset into a three-dimensional physical form with variable height and color. The height profile of this form directly corresponds to changes in the original data values, while the color can be used to mark specific regions or thresholds of the data, providing users with a data entity that can be directly observed and interacted with physically.

[0068] Finally, the data retrieval and mapping module 20 packages the calculated target height and target color values ​​of all luminescent units into a structured control command and sends it to the spectral data materialization matrix through the control interface to drive it to actually present a three-dimensional physical form.

[0069] The navigation control module 30 is configured to track the real-time attitude of the multimodal material sampling probe in order to control the data cursor to navigate in three-dimensional physical form;

[0070] The navigation control module 30 is activated after the system completes the initial rendering of its three-dimensional physical form. This module receives and stores the initial attitude quaternions from the input signal processing module 10. Subsequently, the module continuously receives real-time attitude quaternions generated by its inertial measurement unit from the multimodal matter sampling probe. .

[0071] The primary task of the navigation control module 30 is to calculate the relative attitude change of the probe. This calculation is performed using the initial and final attitude quaternions. With initial attitude quaternion This is achieved through inverse multiplication, yielding the relative attitude quaternion. :

[0072] ;

[0073] in, It is the conjugate of the initial attitude quaternion. For a unit quaternion, its conjugate is equal to its inverse.

[0074] Obtain the relative attitude quaternion Then, the navigation control module 30 converts it into Euler angles. Specifically, the module extracts the roll angle related to the horizontal plane motion from it. and pitch angle These two angle values ​​are directly used to calculate the position of the data cursor on the two-dimensional plane of the spectral data materialization matrix.

[0075] In one specific embodiment, the position of the data cursor Calculated using the following formula:

[0076] ;

[0077] in, For time; for The cursor position at any given moment;

[0078] and Its coordinate components;

[0079] and To obtain relative attitude quaternions The roll and pitch angles were calculated in the middle;

[0080] The preset initial center position of the cursor, for example, can be set to... ;

[0081] and This is a preset attitude sensitivity coefficient used to adjust the proportional relationship between the probe tilt angle and the vernier displacement distance;

[0082] and These represent the number of units in the horizontal and vertical dimensions of the spectral data materialization matrix 200, respectively.

[0083] This is a constraint function used to constrain the calculated coordinate values ​​within the physical boundaries of the matrix.

[0084] Ultimately, the floating-point coordinates need to be converted to integer coordinates that can be addressed on a discrete matrix. The navigation control module 30 processes the calculated floating-point coordinates. Perform a rounding or floor operation to obtain the final integer cursor position. This integer coordinate position is output and transmitted in real time to the haptic feedback generation module 40 for subsequent local data feature extraction.

[0085] The tactile feedback generation module 40 is configured to generate a tactile feedback signal based on local data features of the current position of the data cursor, and send the tactile feedback signal to the multimodal material sampling probe for presentation.

[0086] The haptic feedback generation module 40 is configured to receive the cursor position data, which is an integer data output from the navigation control module 30, in real time. Upon receiving the location, the module performs a local data feature extraction operation. This operation requires access to the heightmap data generated and used by the data retrieval and mapping module 20. The data is a two-dimensional array that stores the height values ​​of all cells in the materialization matrix of the spectral data.

[0087] Specifically, the height map data H is the data retrieval and mapping module 20 in which the one-dimensional scientific detection dataset is processed. Intermediate data structure generated when mapping to a three-dimensional physical form; integer data cursor position It is the output result of the navigation control module 30 after calculating and rounding the probe's real-time attitude.

[0088] The module first extracts amplitude features. This feature is directly defined as the height value of the current position of the data cursor. It is extracted using the received coordinates. As an index, from heightmap data Query the corresponding value in the middle:

[0089] ;

[0090] Simultaneously, the module extracts gradient features. This feature represents the local spatial rate of change of the three-dimensional physical shape at the current position of the data cursor, and its magnitude is obtained by calculating the height gradient magnitude at that point. In a specific embodiment, the central difference method is used to approximate the gradient. First, calculate... direction and partial derivatives of direction and :

[0091] , ;

[0092] To handle boundary conditions, when or When located at the matrix boundary, one-sided differences are used for computation. Subsequently, gradient features are calculated. The value of is determined by the Euclidean norm of these two components:

[0093] ;

[0094] After extracting amplitude features and gradient features Then, the haptic feedback generation module 40 generates a signal to drive the haptic feedback unit based on these two feature values. In a specific embodiment, the instantaneous amplitude of this signal... and instantaneous frequency Modulation is achieved using the following formula:

[0095] ;

[0096] in, For time;

[0097] and They are respectively The instantaneous amplitude and instantaneous frequency of the tactile feedback signal at any given moment;

[0098] The extracted amplitude features;

[0099] The extracted gradient features;

[0100] and This is a preset haptic gain coefficient used to scale the intensity of the influence of data features on haptic feedback;

[0101] and These are preset base amplitude and base frequency, respectively, to ensure that the probe can maintain a perceptible weak base vibration even in regions where the data characteristic value is zero.

[0102] Finally, the module will calculate the instantaneous amplitude. and instantaneous frequency The tactile control command data packet is encapsulated into a structured data packet. This data packet is sent to the multimodal material sampling probe via the wireless communication interface of the central processing system to drive its tactile feedback unit to generate vibrations with specific physical properties. This process is continuously executed in a high-frequency loop to ensure that the tactile feedback remains synchronized with the probe's navigation operations.

[0103] See attached document Figure 4 This is a flowchart of an intelligent interactive method for border security education in the detection of hazardous substances in imported goods, according to an embodiment of the present invention. The method includes the following steps:

[0104] S401: The user holds a multimodal material sampling probe and makes physical contact with a specific sampling point on the physical product model to be tested or brings it within a preset interaction distance.

[0105] S402, the multimodal material sampling probe performs composite signal acquisition.

[0106] Specifically, its internal near-field communication reader reads sample identifiers from the model of the physical commodity under test;

[0107] Its internal photoelectric sensor identifies the sampling point identifier from the sampling point;

[0108] Its internal inertial measurement unit collects the probe's attitude at the current moment as the initial attitude quaternion. .

[0109] The S403, the internal microcontroller of the multimodal material sampling probe, encapsulates the acquired sample identifier, sampling point identifier, and initial attitude quaternion into a structured input signal data packet, and sends it to the central processing system through its wireless communication module.

[0110] S404, the input signal processing module 10 of the central processing system receives and parses the input signal data packet. After verifying the validity of the data, it distributes the sample identifier and sampling point identifier to the data retrieval and mapping module 20, and sets the initial attitude quaternion. Distribute to navigation control module 30.

[0111] S405, the data retrieval and mapping module 20 uses the received sample identifier and sampling point identifier as search keywords to query and obtain a corresponding one-dimensional scientific detection dataset from a preset database. .

[0112] S406, Data retrieval and mapping module 20 executes the mapping algorithm to transform the one-dimensional scientific detection dataset. This is converted into a set of two-dimensional instructions, which contains the target height and target color values ​​for each luminescent unit in the spectral data materialization matrix. This instruction set is then sent to the spectral data materialization matrix.

[0113] S407, the matrix controller of the spectral data materialization matrix, receives and executes a set of instructions, and presents itself as a matrix corresponding to the dataset by controlling the linear actuators and light sources of each luminescent unit in its array. The corresponding three-dimensional physical form. At this point, the system has completed initialization and entered the interactive state.

[0114] The S408 allows users to navigate by changing the attitude of a handheld multimodal matter sampling probe while observing the three-dimensional physical form. The probe's inertial measurement unit continuously acquires the probe's real-time attitude quaternions at a preset frequency. And send it to the central processing system.

[0115] S409, the navigation control module 30 of the central processing system receives real-time attitude quaternions. And based on the stored initial pose quaternion Calculate the integer coordinate position of the data cursor in the three-dimensional physical shape. .

[0116] S410, the haptic feedback generation module 40 of the central processing system receives data cursor position. Based on this, the amplitude feature of that location is extracted from the stored height map. and gradient features Subsequently, the module calculates the instantaneous amplitude of the haptic feedback signal based on these two feature values. and instantaneous frequency .

[0117] S411, the tactile feedback generation module 40 encapsulates the calculated instantaneous amplitude and frequency parameters into a tactile control command and sends it to the multimodal material sampling probe via wireless communication.

[0118] In S412, the internal microcontroller of the multimodal material sampling probe receives tactile control commands and drives its tactile feedback unit to generate physical vibrations that match the command parameters, thereby providing tactile feedback of local data features to the user. This process continues to execute, achieving real-time synchronization between visual navigation and tactile feedback.

[0119] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Identical components are represented by the same reference numerals. Therefore, all equivalent changes made to the structure, shape, and principle of this application should be covered within the scope of protection of this application.

Claims

1. A smart interactive system for border security education on the detection of hazardous substances in imported goods, characterized in that: include: The input signal processing module is configured to receive an input signal related to the model of the physical commodity under test, generated by a multimodal material sampling probe. The data retrieval and mapping module is configured to retrieve a scientific testing dataset from the database based on the input signal, and control the spectral data materialization matrix to present the scientific testing dataset as a three-dimensional physical form. The navigation control module is configured to track the real-time attitude of the multimodal material sampling probe in order to control the data cursor to navigate on the three-dimensional physical shape. The tactile feedback generation module is configured to generate a tactile feedback signal based on local data features of the current position of the data cursor, and send the tactile feedback signal to the multimodal material sampling probe for presentation.

2. The intelligent interactive system for border security science popularization on the detection of hazardous substances in imported goods according to claim 1, characterized in that, The multimodal material sampling probe includes: A near-field communication reader is used to identify the physical product model to be tested; An inertial measurement unit is used to acquire the real-time attitude of the multimodal material sampling probe; A tactile feedback unit is used to generate physical vibrations based on the tactile feedback signal.

3. The intelligent interactive system for border security science popularization on the detection of hazardous substances in imported goods according to claim 1, characterized in that, The spectral data materialization matrix includes an array of multiple independently controllable luminescent units. The physical height and emission color of the luminescent units are controlled by the data retrieval and mapping module to jointly constitute the three-dimensional physical form.

4. The intelligent interactive system for border security science popularization on the detection of hazardous substances in imported goods according to claim 1, characterized in that, The input signal is a composite input signal, which includes a unique identifier and a sampling point identifier; The data retrieval and mapping module retrieves the scientific testing dataset based on the combination of the unique identifier and the sampling point identifier.

5. The intelligent interactive system for border security science popularization on the detection of hazardous substances in imported goods according to claim 1, characterized in that, The navigation control module determines the position of the data cursor on the three-dimensional physical shape by calculating the change in the real-time attitude of the multimodal material sampling probe relative to its initial attitude.

6. The intelligent interactive system for border security science popularization on the detection of hazardous substances in imported goods according to claim 5, characterized in that, The position of the data cursor is determined by the roll and pitch angles of the multimodal material sampling probe, and its calculation method includes: ； in, For time, for The position of the data cursor at any given time. and Its coordinate components, and They are respectively The roll and pitch angles at any given moment. This is the initial position of the cursor. and This is the attitude sensitivity coefficient. and The size boundary of the materialization matrix of the spectral data. Let be a constraint function, when the variable exist Return when within the interval ,when Time return ,when Time return .

7. The intelligent interactive system for border security science popularization on the detection of hazardous substances in imported goods according to claim 1, characterized in that, The local data features include: Amplitude characteristics , corresponding to the data cursor in The height of the three-dimensional physical form at the current position; Gradient features The corresponding three-dimensional physical form is in the data cursor at The rate of change of the local space at the current position at any given time.

8. The intelligent interactive system for border security science popularization on the detection of hazardous substances in imported goods according to claim 7, characterized in that, The instantaneous amplitude of the tactile feedback signal generated by the tactile feedback generation module is modulated by the amplitude feature, and its instantaneous frequency is modulated by the gradient feature. The generation method includes: ； in, For time, for Momentary tactile feedback signals and They are respectively Instantaneous amplitude and instantaneous frequency at time 1 / 2. and They are respectively Amplitude and gradient characteristics at time intervals, and This is the tactile gain coefficient. and These are the fundamental amplitude and the fundamental frequency, respectively.

9. The intelligent interactive system for border security science popularization on the detection of hazardous substances in imported goods according to claim 1, characterized in that, The input signal also includes the initial posture of the multimodal material sampling probe when interacting with the physical commodity model under test.

10. A smart interactive method for border security education on the detection of hazardous substances in imported goods, as described in any one of claims 1-9, characterized in that, Includes the following steps: A multimodal material sampling probe is used to interact with the physical product model to generate an input signal; The system receives the input signal, retrieves the scientific testing dataset corresponding to the model of the entity to be tested, and controls the spectral data materialization matrix to present the scientific testing dataset as a three-dimensional physical form. Establish a data resonance feedback closed loop, in which: The real-time attitude of the multimodal material sampling probe is tracked to control the data cursor to navigate on the three-dimensional physical shape; Based on the local data features of the current position of the data cursor, a tactile feedback signal is generated; The tactile feedback signal is transmitted to the multimodal material sampling probe for presentation.

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