A customs intelligent cargo security inspection system and method based on artificial intelligence

Abstract

The present invention relates to the technical field of customs cargo security inspection, and specifically discloses an artificial intelligence-based customs intelligent cargo security inspection system and method. The system comprises: a radioactive detection sensor, which is used to perform radioactive detection on cargo in a container entering the customs; a state monitoring module, which is used to collect environmental information of the cargo during storage; data is collected by the radioactive detection sensor and the state monitoring module, and then the analysis and processing module calculates and analyzes the data. Through such an arrangement, after excluding the influence of environmental factors, the analysis and processing module can accurately calculate the risk coefficient of the cargo containing radioactivity during storage, and judge whether the risk value of the cargo containing radioactivity exceeds the standard during storage, so as to avoid the situation that the staff makes a misjudgment due to environmental factors, and can avoid the situation that the cargo containing radioactivity causes harm to the staff during transportation.

Description

Technical Field

[0001] The present invention relates to the technical field of customs cargo security inspection, and in particular to an artificial intelligence-based customs intelligent cargo security inspection system and method. Background Art

[0002] Customs inspection is a national administrative activity that supervises and inspects inbound and outbound goods, postal items, luggage, currency, gold and silver, securities and means of transport, and collects tariffs. It is an inspection measure taken to safeguard national sovereignty and interests, protect national economic development, crack down on smuggling and violations, and prevent the entry of items contaminated with viruses and bacteria.

[0003] The goods entering and leaving the country include goods that are radioactive in nature. The uses of radioactive materials are wide and varied, covering many fields such as medicine, energy, scientific research, and industry. However, the volatile substances of radioactive materials are harmful to the human body and the environment. Therefore, when conducting security checks on radioactive goods, the radioactive goods are usually placed in a sealed space. At the same time, professional personnel are arranged to detect the radioactive substances in the goods and assess their risk. Low-risk goods can enter the country, while high-risk goods are judged as dangerous goods and are not allowed to enter the country.

[0004] In the prior art, when testing radioactive goods, since the goods are usually placed in containers, the temperature and humidity in the containers will affect the radioactivity of the goods, causing the staff to misjudge the risk of the goods and be unable to determine whether the radioactivity will exceed the standard during subsequent transportation, thereby causing harm to the transportation personnel. Summary of the invention

[0005] The purpose of the present invention is to provide a customs intelligent cargo security inspection system and method based on artificial intelligence to solve the following technical problems:

[0006] How to avoid the situation where the temperature and humidity in the container affect the radioactivity of the goods during inspection, causing the staff to misjudge the risk of the goods.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] An artificial intelligence-based customs intelligent cargo security inspection system and method, the system comprising:

[0009] Radioactive detection sensors are used to detect radioactive substances in containers entering customs;

[0010] The status monitoring module is used to collect environmental information of goods during storage;

[0011] An analysis and processing module, configured to compare the information of the goods collected with the status information and the standard information of the goods, judge the risk level of the goods according to the comparison information, and issue an order according to the risk level of the goods;

[0012] An execution module, configured to receive the order issued by the analysis and processing module and process the goods according to the order information.

[0013] Furthermore, a plurality of groups of radioactive detection sensors are provided, and the plurality of groups of radioactive detection sensors are evenly arranged around the goods, and the data monitored by the status monitoring module includes environmental temperature and humidity.

[0014] Furthermore, the process of the analysis and processing includes:

[0015] Through the formula Calculate the coefficient of variation S of the radiation intensity of the radioactive goods in the container;

[0016] If S≥S0, then let

[0017] If S<S0, then let

[0018] Through the radiation intensity at the i-th radioactive detection position Calculate the risk of the radioactive goods in the container;

[0019] Among them, m is the total number of radioactive detection positions, i = [1, m], is the radiation intensity at the i-th radioactive detection position, S0 is the preset coefficient of variation of the radioactivity of the radioactive goods, is for all The average value of, is for all The maximum value in.

[0020] Furthermore, the process of calculating the risk of the radioactive goods includes:

[0021] Through the formula Calculate the actual risk value coefficient of the radioactive goods in the container

[0022] Among them, f T is the temperature influence function, f Y is the humidity influence function, T is the actual storage temperature of the radioactive goods in the container, T0 is the standard storage temperature of the radioactive goods in the container, Y is the actual storage humidity of the radioactive goods in the container, Y0 is the standard storage humidity of the radioactive goods in the container, and X1 and X2 are the weight coefficients of the storage temperature and humidity of the radioactive goods in the container respectively;

[0023] The actual risk value coefficient of the radioactive cargo in the container The actual risk factor of the radioactive cargo is Make a comparison;

[0024] like The risk level of radioactive cargo in the container is judged to be high;

[0025] Otherwise, the risk of radioactive cargo in the container is judged to be low.

[0026] Furthermore, the analysis and processing process also includes:

[0027] When it is determined that the risk of radioactive goods in the container is high, the analysis and processing module generates a traceability information code from its information code and issues a command. The execution module receives the command issued by the analysis and processing module and isolates the radioactive goods.

[0028] When it is determined that the risk of radioactive goods in the container is low, an information code is generated through the analysis and processing module, and a command is issued. The execution module receives the command issued by the analysis and processing module to load the goods and monitor the risk change in real time.

[0029] Furthermore, the process of monitoring risk changes includes:

[0030] The real-time data obtained through continuous monitoring of the status monitoring module can establish a real-time change curve of the radiation intensity of radioactive goods and the real-time variation curve δ(t) of environmental conditions;

[0031] Collect data evenly at preset fixed time intervals and δ(t) data;

[0032] And through the formula Calculate the correlation r between the radiation intensity of radioactive cargo and changes in environmental conditions;

[0033] Where n is the total number of data collection times, k = 1, 2, 3...n;

[0034] By comparing the correlation r between the radiation intensity of radioactive cargo and the change of environmental conditions with the preset correlation threshold r1;

[0035] If r>r1, it is judged that the radiation intensity of radioactive cargo is positively correlated with the change of environmental conditions;

[0036] Otherwise, it is judged that the radiation intensity of radioactive cargo is negatively correlated with the change of environmental conditions;

[0037] Where r∈[0.8, 0.95].

[0038] Furthermore, through the formula Calculate the real-time change curve of environmental conditions;

[0039] Among them, T(t) is the real-time change curve of temperature, Y(t) is the real-time change curve of humidity, μ1 and μ2 are weight coefficients, T0(t) and Y0(t) are the reference values ​​of T(t) and Y(t), respectively.

[0040] Furthermore, the process of monitoring risk changes also includes:

[0041] By formula Calculate the average risk factor β of radioactive cargo during storage;

[0042] in, is the maximum radiation level of radioactive cargo, is the minimum radiation level of radioactive cargo, and g is the proportionality coefficient;

[0043] Compare the average risk factor β of the radiation intensity with the standard average risk factor β1 of the radiation intensity;

[0044] If β>β1, it is judged that the average risk of radioactive cargo during storage is high;

[0045] Otherwise, the average risk of radioactive cargo during storage is judged to be low.

[0046] A customs intelligent cargo security inspection method based on artificial intelligence, the method comprising:

[0047] S1: Radioactivity detection of goods in containers entering customs is carried out through radioactivity detection sensors;

[0048] S2: Collect environmental information of goods during storage through the status monitoring module;

[0049] S3: The collected cargo information is compared with the status information and the cargo standard information through the analysis and processing module, the risk level of the cargo is determined based on the comparison information, and an order is issued;

[0050] S4: The execution module receives the command issued by the analysis and processing module, and processes the goods according to the command information.

[0051] Beneficial effects of the present invention:

[0052] (1) The present invention collects data through the radioactive detection sensor and the status monitoring module, and then the analysis and processing module calculates and analyzes the data. Through such an arrangement, after excluding the influence of environmental factors, the analysis and processing module can accurately calculate the risk factor of radioactive goods during the storage process, and determine whether the risk value of radioactive goods will exceed the standard during the storage process, thereby avoiding the situation where the staff makes a misjudgment due to environmental factors, and avoiding the situation where the radioactive goods cause harm to the staff during the transportation process.

[0053] (2) The present invention calculates the dispersion coefficient S of the radiation intensity of the radioactive goods in the container. If the dispersion coefficient is larger, the risk of the goods is judged to be greater, indicating that some of the goods in the container have strong radioactivity. If the dispersion coefficient is smaller, the risk of the goods is judged to be smaller. The risk of the radioactive goods in the container is calculated by the radioactivity intensity at any radioactivity detection position, and the risk of the goods is further judged.

[0054] (3) The present invention can obtain the actual risk value coefficient of radioactive cargo in the container after eliminating the influence of temperature and humidity. And through the actual risk value coefficient of the radioactive cargo in the container The actual risk factor of the radioactive cargo is By comparing the radioactive cargo in the container, the risk level of the cargo can be determined, so as to avoid the situation where the temperature and humidity in the container will affect the radioactivity level of the cargo during the inspection, causing the staff to misjudge the risk level of the cargo.

[0055] (4) The present invention determines the risk value of radioactive goods through the analysis and processing module. When the risk level of radioactive goods in the container is too high, the analysis and processing module will generate a traceability information code from its information code and issue a detention order. The execution module receives the order issued by the analysis and processing module and intercepts and isolates the radioactive goods. When the risk level of radioactive goods in the container is relatively low, the analysis and processing module will generate an information code and issue a continuous monitoring order. The execution module receives the order issued by the analysis and processing module and loads the goods, and monitors the risk level changes in real time.

[0056] (5) The present invention determines the average risk level of radioactive goods during storage by comparing the average risk coefficient β of radiation intensity with the standard average risk coefficient β1 of radiation intensity. If β>β1, it is determined that the average risk level of the radioactive goods during storage is high, and the analysis and processing module issues a retention order. The execution module receives the order and isolates the high-risk radioactive goods. If β<β1, it is determined that the average risk level of the radioactive goods during storage is low. The analysis and processing module issues a loading order. The execution module receives the order and loads and transports the low-risk radioactive goods. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The present invention will be further described below in conjunction with the accompanying drawings.

[0058] Figure 1 It is a schematic block diagram of an artificial intelligence-based customs intelligent cargo security inspection system in the present invention;

[0059] Figure 2 The present invention is a flowchart of the steps of an artificial intelligence-based customs intelligent cargo security inspection method. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] See also Figure 1 As shown, in one embodiment, the present application provides a customs intelligent cargo security inspection system and method based on artificial intelligence, the system comprising:

[0062] Radioactive detection sensors are used to detect radioactive substances in cargo containers entering customs;

[0063] The status monitoring module is used to collect environmental information of goods during storage;

[0064] An analysis and processing module is used to compare the collected cargo information with the status information and the cargo standard information, determine the cargo risk level based on the comparison information, and issue an order based on the cargo risk level;

[0065] The execution module is used to receive the command issued by the analysis and processing module and process the goods according to the command information;

[0066] Through the above technical solution, a radioactive detection sensor and an analysis and processing module are set in the system of this embodiment. The radioactive detection sensor is used to detect the radioactivity of the goods in the container entering the customs, and the goods are classified according to whether they are radioactive. Then, the risk value of the radioactive goods is compared with the preset risk threshold through the analysis and processing module. Then, the risk coefficient of the radioactive goods is determined according to the analysis and comparison results, and the high-risk radioactive goods are intercepted to avoid the high-risk radioactive goods entering the customs and causing harm in the subsequent transportation process.

[0067] In the above scheme, the state monitoring module can monitor the changes in the environmental data of the radioactive goods during storage, and transmit the data to the analysis and processing module in real time, and then the analysis and processing module calculates and analyzes the data. Through such a setting, after excluding the influence of environmental factors, the analysis and processing module can accurately calculate the risk coefficient of the radioactive goods during the storage process, and judge whether the risk value of the radioactive goods will exceed the standard during the storage process, so as to avoid the staff from making misjudgments due to environmental factors, and avoid the radioactive goods from causing harm to the staff during the transportation process;

[0068] The data acquired by the status monitoring module can be obtained by connecting the system to relevant detection equipment. The data acquisition method can be completed through existing technologies. Radioactive detection sensors are existing technologies and will not be described in detail here.

[0069] The radioactivity detection sensors are provided in multiple groups, and the multiple groups of radioactivity detection sensors are evenly arranged around the cargo, and the data monitored by the status monitoring module include ambient temperature and humidity;

[0070] Through the above technical solution, when the goods enter the customs, multiple groups of radioactive detection sensors arranged on the outside of the container will detect whether the goods are radioactive. If there is radioactivity in the goods, the data will be transmitted to the analysis and processing module. The analysis and processing module will issue a command to the indication module according to the data. The indication module will classify the goods according to the command issued by the analysis and processing module. After that, the analysis and processing module will compare and analyze the risk value of the radioactive goods with the preset risk threshold, and intercept the goods with high risk coefficients, and continuously observe the goods with low risk coefficients.

[0071] In the above scheme, the status monitoring module can monitor the temperature, humidity and amount of radioactive materials of low-risk goods in real time during storage, and determine whether the risk value of radioactive goods exceeds the standard during storage through the analysis and processing module.

[0072] The analysis and processing process includes:

[0073] Calculate the coefficient of variation S of the radiation intensity of radioactive goods in the container through the formula ;

[0074] If S≥S0, then let

[0075] If S<S0, then let

[0076] Calculate the risk of radioactive goods in the container through the radiation intensity at the i-th radioactive detection position;

[0077] where m is the total number of radioactive detection positions, i = [1, m], is the radiation intensity at the i-th radioactive detection position, S0 is the preset coefficient of variation of the radioactivity of radioactive goods, is for all average value of, is for all the maximum value in;

[0078] Through the above technical solution, the formula can be used to calculate the coefficient of variation S of the radiation intensity of radioactive goods in the container. At this time, if the coefficient of variation is larger, it is judged that the risk degree of the goods is larger, indicating that the radioactivity of a part of the goods in the container is stronger. If the coefficient of variation is smaller, it is judged that the risk of the goods is smaller, and the risk of radioactive goods in the container is calculated through the radiation intensity at any radioactive detection position, and the risk degree of the goods is further judged.

[0079] The process of calculating the risk of radioactive goods includes:

[0080] Calculate the actual risk value coefficient of radioactive goods in the container through the formula ;

[0081] where f T is the temperature influence function, and the temperature influence function is obtained by fitting according to the test data. f Y is the humidity influence function, and the humidity influence function is obtained by fitting according to the test data. T is the actual storage temperature of radioactive goods in the container, T0 is the standard storage temperature of radioactive goods in the container, Y is the actual storage humidity of radioactive goods in the container, Y0 is the standard storage humidity of radioactive goods in the container. The standard storage temperature T0 and the standard storage humidity Y0 of the radioactive goods in the container can be set by fitting according to the empirical data. X1 and X2 are the weight coefficients of the storage temperature and humidity of radioactive goods in the container respectively, and the above weight coefficients are set by fitting according to the empirical data;

[0082] The actual risk value coefficient of the radioactive cargo in the container The actual risk factor of the radioactive cargo is Make a comparison;

[0083] like The risk level of radioactive cargo in the container is judged to be high;

[0084] Otherwise, the risk of radioactive cargo in the container is judged to be low;

[0085] Through the above technical solution, this embodiment provides the actual risk value coefficient of radioactive cargo in the container. And the actual risk value coefficient of the preset radioactive cargo The formula for the actual risk value coefficient of radioactive cargo in the container is: Obviously, the temperature and humidity in the container are the main factors affecting radioactivity, so after excluding the influence of temperature and humidity, the actual risk value coefficient of radioactive goods in the container can be obtained. And through the actual risk value coefficient of the radioactive cargo in the container The actual risk factor of the radioactive cargo is By comparing the radioactive cargo in the container, the risk level of the cargo can be determined, so as to avoid the situation where the temperature and humidity in the container will affect the radioactivity level of the cargo during the inspection, causing the staff to misjudge the risk level of the cargo.

[0086] The analysis and processing process also includes:

[0087] When it is determined that the risk of radioactive goods in the container is high, the analysis and processing module generates a traceability information code from its information code and issues a command. The execution module receives the command issued by the analysis and processing module and isolates the radioactive goods.

[0088] When it is determined that the risk level of radioactive goods in the container is low, the analysis and processing module generates an information code and issues a command. The execution module receives the command issued by the analysis and processing module to load the goods and monitors the risk level changes in real time.

[0089] Through the above technical solution, when the risk level of radioactive goods in the container is too high, the analysis and processing module will generate a traceability information code from its information code and issue a detention order. The execution module receives the order issued by the analysis and processing module and intercepts and isolates the radioactive goods. When the risk level of radioactive goods in the container is relatively low, the analysis and processing module will generate an information code and issue a continuous monitoring order. The execution module receives the order issued by the analysis and processing module to load the goods and monitor the changes in risk level in real time.

[0090] The process of monitoring risk changes includes:

[0091] The real-time data obtained through continuous monitoring of the status monitoring module can establish a real-time change curve of the radiation intensity of radioactive goods and the real-time variation curve δ(t) of environmental conditions;

[0092] Collect data evenly at preset fixed time intervals and δ(t) data;

[0093] And through the formula Calculate the correlation r between the radiation intensity of radioactive cargo and changes in environmental conditions;

[0094] Where n is the total number of data collection times, k = 1, 2, 3...n;

[0095] By comparing the correlation r between the radiation intensity of radioactive cargo and the change of environmental conditions with a preset correlation threshold r1, the preset correlation threshold r1 can be set by empirical fitting;

[0096] If r>r1, it is judged that the radiation intensity of radioactive cargo is positively correlated with the change of environmental conditions;

[0097] Otherwise, it is judged that the radiation intensity of radioactive cargo is negatively correlated with the change of environmental conditions;

[0098] Where r∈[0.8, 0.95];

[0099] As an implementation mode of the present invention, this embodiment provides a correlation r between the radiation intensity of radioactive goods and changes in environmental conditions. At this time, the analysis and processing module will compare the correlation r between the radiation intensity of radioactive goods and changes in environmental conditions with a preset correlation threshold r1. If r>r1, it is judged that the radiation intensity of the radioactive goods is positively correlated with the changes in environmental conditions. Otherwise, it is judged that the radiation intensity of the radioactive goods is negatively correlated with the changes in environmental conditions. Since r∈[0.8, 0.95], it means that the environmental conditions in the container are positively correlated with the radiation intensity of the radioactive goods. Then, in the subsequent transportation process, it is only necessary to adjust the environmental conditions to ensure that the radiation intensity of the radioactive goods will not be too high, thereby reducing the risk of radioactive goods during transportation and avoiding the situation where radioactive goods cause harm to workers during transportation.

[0100] By formula Calculate the real-time change curve of environmental conditions;

[0101] Wherein, T(t) is the real-time change curve of temperature, Y(t) is the real-time change curve of humidity, μ1 and μ2 are weight coefficients, T0(t) and Y0(t) are reference values ​​of T(t) and Y(t) respectively, and the above reference values ​​are selected and set according to the allowable temperature error and humidity error in the empirical data, T(t) and Y(t) are real-time change curves established according to the real-time data continuously monitored by the status monitoring module, and the above weight coefficients are set according to the empirical data fitting;

[0102] Through the above technical solution, this embodiment provides a real-time change curve of environmental conditions. Calculation shows that, obviously, the higher the real-time change curve of temperature is and the lower the real-time change curve of humidity is, the higher the change curve of environmental conditions is. This means that in the container, when the temperature is higher and the humidity is lower, the radiation intensity of radioactive goods will increase, thereby increasing the risk of radioactive goods. Therefore, during transportation, ensuring that radioactive goods are kept at low temperature and high humidity can avoid the increase in radiation intensity of radioactive goods, thereby avoiding the risk of radioactive goods during transportation.

[0103] The process of monitoring risk changes also includes:

[0104] By formula Calculate the average risk factor β of radioactive cargo during storage;

[0105] in, is the maximum radiation level of radioactive cargo, is the minimum radiation level of radioactive cargo, g is the proportionality coefficient, which can be set based on empirical data fitting;

[0106] The average risk coefficient β of the radiation intensity is compared with the standard average risk coefficient β1 of the radiation intensity. The standard average risk coefficient β1 of the radiation intensity can be set according to the empirical data fitting;

[0107] If β>β1, it is judged that the average risk of radioactive cargo during storage is high;

[0108] Otherwise, the average risk of radioactive cargo during storage is judged to be low;

[0109] Through the above technical solution, this embodiment provides an average risk coefficient β of radioactive goods during storage, which is used to determine the average risk of radioactive goods during storage. The formula can be used as follows: After calculation, the average risk coefficient of radiation intensity β is compared with the standard average risk coefficient of radiation intensity β1 to judge the average risk of radioactive goods during storage. If β>β1, it is judged that the average risk of radioactive goods during storage is high, and the analysis and processing module issues an interception order, and the execution module receives the order and isolates the high-risk radioactive goods. If β<β1, it is judged that the average risk of radioactive goods during storage is low, and the analysis and processing module issues a loading order, and the execution module receives the order and loads and transports the low-risk radioactive goods.

[0110] See also Figure 2 As shown, a customs intelligent cargo security inspection method based on artificial intelligence, the method comprising:

[0111] S1: Radioactivity detection of goods in containers entering customs is carried out through radioactivity detection sensors;

[0112] S2: Collect environmental information of goods during storage through the status monitoring module;

[0113] S3: The collected cargo information is compared with the status information and the cargo standard information through the analysis and processing module, the risk level of the cargo is determined based on the comparison information, and an order is issued;

[0114] S4: receiving the command issued by the analysis and processing module through the execution module, and processing the goods according to the command information;

[0115] When conducting security inspection on goods entering the customs, firstly, the radioactivity detection sensor is used to detect the radioactivity of the goods in the container entering the customs, and the goods are classified according to whether they are radioactive. Then, the risk value of the radioactive goods is compared with the preset risk threshold through the analysis and processing module, and the risk level of the goods is determined based on the comparison information and a command is issued. The execution module receives the command issued by the analysis and processing module and processes the goods according to the command information.

[0116] Afterwards, the status monitoring module collects the status information of the goods during the storage process, monitors the status of the goods in real time, and determines whether the risk value of the radioactive goods exceeds the standard during the storage process through the analysis and processing module, and issues commands based on the judgment information. The execution module receives the commands issued by the analysis and processing module and processes the goods according to the command information.

[0117] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. An artificial intelligence-based customs intelligent cargo security inspection system, characterized in that: The system comprises: Radioactive detection sensors are used to detect radioactive substances in cargo containers entering customs; The status monitoring module is used to collect environmental information of goods during storage; An analysis and processing module is used to compare the collected cargo information with the status information and the cargo standard information, determine the cargo risk level based on the comparison information, and issue an order based on the cargo risk level; The execution module is used to receive the command issued by the analysis and processing module and process the goods according to the command information; The radioactivity detection sensors are provided in multiple groups, and the multiple groups of radioactivity detection sensors are evenly arranged around the cargo, and the data monitored by the status monitoring module include ambient temperature and humidity; The analysis and processing process includes: By formula Calculate the dispersion coefficient S of the radiation intensity of the radioactive cargo in the container; If S ≥ S0, then let If S < S0, then set The radioactivity intensity at the i-th radioactivity detection position Calculate the risk of radioactive cargo in containers; Where m is the total number of radioactivity detection positions, i = [1, m], is the radioactivity intensity at the i-th radioactivity detection position, S0 is the preset discrete coefficient of radioactivity of radioactive cargo, For all The average value of For all The maximum value in ; The process of calculating the risk of the radioactive cargo includes: By formula Calculate the actual risk factor of radioactive cargo in the container Among them, f T is the temperature influence function, f Y is the humidity influence function, T is the actual storage temperature of the radioactive cargo in the container, T0 is the standard storage temperature of the radioactive cargo in the container, Y is the actual storage humidity of the radioactive cargo in the container, Y0 is the standard storage humidity of the radioactive cargo in the container, X1 and X2 are the weight coefficients of the storage temperature and humidity of the radioactive cargo in the container respectively; The actual risk value coefficient of the radioactive cargo in the container The actual risk factor of the radioactive cargo is Make a comparison; like The risk level of radioactive cargo in the container is judged to be high; Otherwise, the risk of radioactive cargo in the container is judged to be low.

2. According to claim 1, the intelligent customs cargo security inspection system based on artificial intelligence is characterized in that: The analysis and processing process also includes: When it is determined that the risk of radioactive goods in the container is high, the analysis and processing module generates a traceability information code from its information code and issues a command. The execution module receives the command issued by the analysis and processing module and isolates the radioactive goods. When it is determined that the risk of radioactive goods in the container is low, an information code is generated through the analysis and processing module, and a command is issued. The execution module receives the command issued by the analysis and processing module to load the goods and monitor the risk change in real time.

3. According to claim 2, the intelligent customs cargo security inspection system based on artificial intelligence is characterized in that: The process of monitoring risk changes includes: The real-time data obtained through continuous monitoring of the status monitoring module can establish a real-time change curve of the radiation intensity of radioactive goods And the real-time change curve of environmental conditions δ ( t ) ; Collect data evenly at preset fixed time intervals and δ(t) data; And through the formula Calculate the correlation r between the radiation intensity of radioactive cargo and changes in environmental conditions; Where n is the total number of data collection times, k = 1, 2, 3...n; By comparing the correlation r between the radiation intensity of radioactive cargo and the change of environmental conditions with the preset correlation threshold r1; If r>r1, it is judged that the radiation intensity of radioactive cargo is positively correlated with the change of environmental conditions; Otherwise, it is judged that the radiation intensity of radioactive cargo is negatively correlated with the change of environmental conditions; Among them, r∈ [ 0.8, 0.95 ] .

4. According to claim 3, the intelligent customs cargo security inspection system based on artificial intelligence is characterized in that: By formula Calculate the real-time change curve of environmental conditions; Among them, T ( t ) Real-time temperature Change curve, Y ( t ) is the real-time change curve of humidity, μ1 and μ2 are weight coefficients, T 0( t ) and Y 0( t ) T ( t ) and Y ( t ) reference value.

5. According to claim 4, the intelligent customs cargo security inspection system based on artificial intelligence is characterized in that: The process of monitoring risk changes also includes: By formula Calculate the average risk factor β of radioactive cargo during storage; in, is the maximum radiation level of radioactive cargo, is the minimum radiation level of radioactive cargo, and g is the proportionality coefficient; Compare the average risk factor β of the radiation intensity with the standard average risk factor β1 of the radiation intensity; If β>β1, it is judged that the average risk of radioactive cargo during storage is high; Otherwise, the average risk of radioactive cargo during storage is judged to be low.

6. A customs intelligent cargo security inspection method based on artificial intelligence, characterized in that: The method adopts the artificial intelligence-based customs intelligent cargo security inspection system as claimed in claim 1, and the method comprises: S1: Radioactivity detection of goods in containers entering customs is carried out through radioactivity detection sensors; S2: Collect environmental information of goods during storage through the status monitoring module; S3: The collected cargo information is compared with the status information and the cargo standard information through the analysis and processing module, the risk level of the cargo is determined based on the comparison information, and an order is issued; S4: The execution module receives the command issued by the analysis and processing module, and processes the goods according to the command information.

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