Quarantine data acquisition and integration method and system

Abstract

The invention provides a quarantine data acquisition and integration method and system, and the method comprises the steps: pre-configuring an API interface corresponding to a quarantine processing system, judging the commodity type of a target quarantine commodity, and carrying out the calling of the API interface corresponding to the quarantine processing system according to the commodity type; obtaining quarantine processing data of different quarantine processing systems for each quarantine commodity by using API interfaces of different quarantine processing systems, wherein the quarantine processing data comprises quarantine pre-processing data and quarantine post-processing data; performing standardized data integration on the quarantine processing data of different quarantine processing systems to obtain standardized quarantine processing data, and further performing data analysis and calculation on the standardized quarantine processing data; quarantine data of the corresponding target quarantine commodity before quarantine processing and after quarantine processing are obtained respectively, the quarantine data before quarantine processing and after quarantine processing are further detected and analyzed, and the quarantine processing effect of the current target quarantine commodity is judged.

Description

Technical Field

[0001] The present invention relates to the technical field of quarantine data collection, and in particular to a quarantine data collection and integration method and system. Background Art

[0002] At present, the invasion of alien species has become a global environmental problem. Prevention and control of alien species invasion and protection of biodiversity are important links in building a strong biosafety barrier. The General Administration of Customs emphasized the importance of maintaining national security, continuously improving the effectiveness of risk prevention and control, and strictly implementing the monitoring, testing and preventive disinfection supervision of imported cold chain food, agricultural products and high-risk non-cold chain container goods.

[0003] Quarantine treatment refers to measures taken on inbound and outbound goods, vehicles, containers and other quarantine objects using biological, physical, chemical and other methods, with the aim of eliminating epidemic risks or potential hazards, and preventing the spread of human infectious diseases and the introduction and export of animal and plant diseases and pests. This measure is an important part of entry-exit inspection and quarantine, and is of great significance for ensuring public health and ecological security.

[0004] The processing method of quarantine data in the prior art is mainly to track and process quarantine data for human targets. The data processing of quarantine items themselves is still a separate identification process, and is dependent on the data processing of human targets, such as the existing published patent CN114420305A. In this patent, the quarantine data analysis platform for entry and exit personnel is used to analyze quarantine data. However, the data of the objects carried by the entry and exit personnel themselves under different quarantine conditions are not integrated and analyzed. Therefore, the prior art still has a large loophole in the quarantine process and cannot be accurately analyzed. Summary of the invention

[0005] One of the inventive purposes of the present invention is to provide a quarantine data collection and integration method and system, wherein the method and system collect different quarantine data, and integrate the collected different quarantine data, perform data analysis and judgment after performing data analysis on the integrated quarantine data, and provide effective risk warnings for possible species invasions and disease transmission, thereby greatly improving the analysis and prevention and control effects of border quarantine.

[0006] Another object of the present invention is to provide a quarantine data collection and integration method and system, wherein the method and system detect, analyze and process diversified quarantine data based on commodities. The present invention utilizes a central control system to connect different types of quarantine processing systems, obtains the parameters of corresponding equipment in the quarantine processing system for data extraction, and integrates the data of different quarantine processing systems through different APIs, and forms standardized and unified quarantine data with the parameters of corresponding equipment in the quarantine processing system. Through the standardized and unified quarantine data of the integrated API, risk analysis of quarantine data is performed, thereby improving the effect of quarantine risk analysis and control.

[0007] Another inventive object of the present invention is to provide a quarantine data collection and integration method and system. After obtaining the corresponding quarantine commodities, the method and system extract and analyze the quarantine data of the quarantine commodities before and after processing. After comparing and analyzing the quarantine data before and after processing of the quarantine commodities, the quarantine treatment effect of the quarantine treatment system itself can be effectively judged, and the treatment effects of different quarantine treatment systems can be comprehensively compared and analyzed, and the effect of the diversified quarantine treatment can be judged in an intuitive indexed form.

[0008] In order to achieve at least one of the above-mentioned invention objects, the present invention further provides a quarantine data collection and integration method, the method comprising the following steps: Pre-configure the API interface corresponding to the quarantine processing system, determine the commodity type of the target quarantine commodity, and call the API interface corresponding to the quarantine processing system according to the commodity type; Using API interfaces of different quarantine processing systems to obtain quarantine processing data of each quarantined commodity by different quarantine processing systems, wherein the quarantine processing data includes pre-quarantine processing data and post-quarantine processing data; Performing standardized data integration on the quarantine processing data of the different quarantine processing systems to obtain standardized quarantine processing data, and further performing data analysis and calculation on the standardized quarantine processing data; After analysis and calculation, the quarantine data of the corresponding target quarantined commodity before and after quarantine treatment are obtained respectively, and the quarantine data before and after quarantine treatment are further tested and analyzed to determine the quarantine treatment effect of the current target quarantined commodity.

[0009] According to one of the preferred embodiments of the present invention, the different quarantine treatment systems include: a channel-type radioactivity detection system, a channel-type outer box spray disinfection system, a fumigation warehouse system, a biomedical waste high-temperature sterilization system and a harmless treatment system; wherein a highly structured XML API interface is configured for each of the different treatment systems, and the XML API interface is used to obtain numerical data of different data types in the different quarantine treatment systems, and the numerical data of the different data types are subjected to standardized data processing to obtain the standardized quarantine treatment data, and data analysis is performed based on the standardized quarantine treatment data.

[0010] According to another preferred embodiment of the present invention, a data processing method for standardizing numerical data obtained by the XML API interface includes: encapsulating a method for identifying quarantine commodity categories in the XML API interface, and configuring a key-value pair list of numerical data corresponding to the commodity category in the XML API interface, wherein the key name key in the key-Value pair is the quarantine type of the corresponding quarantine commodity, and the Value is the quarantine numerical value of the corresponding quarantine commodity, and structured data based on quarantine commodities are constructed using the key-value pair list encapsulated by the XML API interface, wherein a unique identifier is configured for each target quarantine commodity, the corresponding key-value pair list is called based on the unique identifier and the identified quarantine commodity type, and the corresponding quarantine data is automatically obtained as the key value according to the key name of the key-value pair list.

[0011] According to another preferred embodiment of the present invention, a data processing method for standardizing the numerical data obtained by the XML API interface includes: encapsulating a standardized numerical conversion method based on multivariate quarantine data in the XML API interface, specifically including the following steps: obtaining the maximum quarantine data S of the target commodity type according to the key name in the key-Value list of the key-value pair; max and minimum quarantine data S min , and calculate the standard deviation σ of different quarantine data S for each commodity type, and perform standardization according to the standard deviation according to the following formula: , where M i represents the standardized quarantine data of different quarantine data i corresponding to the commodity type, represents the average value of the quarantine data of the corresponding commodity type, and the standardized quarantine data M of different quarantine data i of the corresponding commodity type i The key-value list is stored according to the key value encapsulated by the XML API interface to obtain highly structured and standardized quarantine processing data M i .

[0012] According to another preferred embodiment of the present invention, after obtaining the standardized quarantine processing data M corresponding to the commodity type, i After that, the standardized quarantine processing data M is further processed. i Perform data integration and analysis, and standardize quarantine processing data M according to the following formula i Integrated analysis of: P= , where y i and w i are respectively based on the standardized quarantine processing data M i Corresponding to the pre-quarantine data and post-quarantine data of the commodity type; P represents the integrated analysis result data of the multivariate quarantine data of the same target commodity type, e is the natural constant, and σ is the standard deviation.

[0013] According to another preferred embodiment of the present invention, the risk warning level V is configured based on the integrated analysis result data P of the multi-element quarantine data. j , where j is the corresponding level value, and the corresponding risk warning level V is pre-configured j quarantine control strategy, when the integrated analysis result data P of the multivariate quarantine data meets the corresponding risk warning level V j , then execute the corresponding quarantine control strategy; Build an automated parameter modulation model: ,in, are intercept one and intercept two, are regression coefficients one and two, are error term 1 and error term 2; are input variable one and input variable two; Import the preset risk warning level configuration table, and determine the values ​​of error one and error two according to the risk warning level configuration table.

[0014] According to another preferred embodiment of the present invention, the standardized quarantine processing data M corresponding to the commodity type obtained through the XML API interface i After that, obtain the equipment parameters f corresponding to the quarantine process i and environmental parameters r i , and according to the device parameter f i and environmental parameters r i According to the corresponding risk warning level V j Automatic parameter modulation is performed to make the final risk warning level meet the quarantine requirements, wherein the equipment parameters include channel-type radioactive detection equipment parameters, channel-type outer box spray disinfection equipment parameters, fumigation warehouse equipment parameters, biomedical waste high temperature sterilization equipment parameters, harmless treatment equipment parameters, and environmental parameters r i Including temperature, humidity and air pressure.

[0015] According to another preferred embodiment of the present invention, after completing the corresponding standardized quarantine processing data M i After analysis, the risk warning level V is pre-configured j The numerical range v is obtained based on the corresponding integrated analysis result data P, and the quarantine data i of the corresponding commodity type are evaluated in different dimensions, and a comprehensive evaluation is performed by weighted summation to obtain quarantine data evaluation results of different dimensions.

[0016] In order to achieve at least one of the above-mentioned purposes of the invention, the present invention further provides a quarantine data collection and integration system, which executes the above-mentioned quarantine data collection and integration method.

[0017] The present invention further provides a computer-readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above-mentioned quarantine data collection and integration method. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Shown is a schematic flow chart of a quarantine data collection and integration method in the present invention. DETAILED DESCRIPTION

[0019] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations. The basic principles of the present invention defined in the following description can be applied to other embodiments, variations, improvements, equivalents, and other technical solutions that do not deviate from the spirit and scope of the present invention.

[0020] It is to be understood that the term "one" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of an element may be one, while in another embodiment, the number of the element may be multiple, and the term "one" should not be understood as a limitation on the quantity.

[0021] Please combine Figure 1The present invention discloses a quarantine data collection and integration method and system, which is mainly aimed at quarantine methods for imported and exported animals and plants, chilled and fresh products, wherein the method of the present invention includes but is not limited to the detection of pathogens, parasites, and harmful organisms carried by animals, plants, chilled and fresh products, and their products, and processes the detection results. Since the types of quarantine processing data are different, and different quarantine processing data require different quarantine processing systems to acquire and process data, the present invention performs data analysis on the quarantine processing data of the different quarantine processing systems to determine whether there is a quarantine risk and evaluate the effect of the quarantine processing results. The specific method includes the following steps:

[0022] S01. Pre-configure an API interface corresponding to the quarantine processing system, determine the commodity type of the target quarantine commodity, and call the API interface of the corresponding quarantine processing system according to the commodity type; S02. Using API interfaces of different quarantine processing systems, obtaining quarantine processing data of each quarantined commodity by different quarantine processing systems, wherein the quarantine processing data includes pre-quarantine processing data and post-quarantine processing data; S03, performing standardized data integration on the quarantine processing data of the different quarantine processing systems to obtain standardized quarantine processing data, and further performing data analysis and calculation on the standardized quarantine processing data; S04. After analysis and calculation, the quarantine data of the corresponding target quarantined commodity before and after quarantine treatment are obtained respectively, and the quarantine data before and after quarantine treatment are further tested and analyzed to determine the quarantine treatment effect of the current target quarantined commodity.

[0023] It should be noted that the quarantine method in the present invention is based on quarantined commodities. Due to the quarantine of different quarantined products, the different quarantine treatment systems include: a channel-type radioactive detection system, a channel-type outer box spray disinfection system, a fumigation warehouse system, a high-temperature sterilization system for biomedical waste, and a harmless treatment system; the method for determining the commodity type of the target quarantined commodity can adopt physical radio frequency tag recognition or be based on existing mature image recognition models, such as including but not limited to the YOLO model.

[0024] In one of the preferred embodiments of the present invention, an RFID reader is configured in the corresponding quarantine system, and an RFID tag is attached to the corresponding quarantined commodity. By setting the reading range of the RFID reader, when the RFID tag of the corresponding quarantined commodity is detected, the RFID reader can identify the RFID tag within the detection range, thereby identifying the type of the corresponding quarantined commodity. This method is efficient and accurate, and is particularly suitable for rapid identification of large quantities of commodities.

[0025] Using the YOLO model as a target detection model, the type of quarantined goods on the corresponding quarantine system path can be identified. By collecting and analyzing images of quarantined goods, the system can automatically obtain the quarantine result data for that type of goods. This method not only improves quarantine efficiency, but also reduces the possibility of human error.

[0026] In the quarantine system, the radioactivity detection system detects the radioactivity data of the target quarantined commodity, wherein the unit of the radioactivity data may be microsievert / hour (μSv / h). Before the target quarantined commodity passes through the channel-type outer box spray disinfection system, the pathogen detection data includes but is not limited to the bacterial content per unit area, or the pathogen content per unit volume of liquid, wherein the unit of the pathogen content detection data may be CFU / L (colony forming unit / liter), and the pathogen is detected after the target quarantined commodity passes through the channel-type outer box spray disinfection system, that is, the pre-quarantine data and post-quarantine data may be obtained. When the target quarantined commodity passes through the fumigation warehouse system, the microbial content data of the target commodity before fumigation may be detected as the pre-quarantine data, and the microbial content of the target commodity after fumigation may be detected as the post-quarantine data. The unit of the microbial content may be CFU / L (colony forming unit / liter). It should be noted that due to the different types of target commodities, different types of target commodities need to pass through different quarantine channels. Not all types of target commodities pass through the same quarantine channel. The selection of the quarantine channel needs to be set according to the nature of the goods. For example, the target commodity type for the quarantine channel of the fumigation warehouse system is generally for grains, dried fruits, tea and other commodities that are prone to mildew, or wood or textiles that are susceptible to mold and pests. As for the channel-type outer box spray disinfection system, it is generally aimed at commodities with outer packaging, and the surface of commodities with outer packaging may be contaminated with pathogens or toxic and harmful substances. Spray disinfection is a relatively convenient quarantine treatment method. The same is true for the high-temperature sterilization system and harmless treatment system for biomedical waste.

[0027] It is worth mentioning that, since different quarantine systems have different data types and data units, and it is difficult to exchange data between different data types, the present invention performs the following data processing on the relevant quarantine data of different quarantine systems: highly structured XML API interfaces are configured for the different quarantine processing systems respectively, and the XML API interfaces in the different quarantine processing systems correspond to the URLs of the systems, and the URL addresses of the systems corresponding to the XML API interfaces are the detection data and quarantine processing result data of the corresponding quarantine systems, wherein the XML API interfaces pre-encapsulate the XML files that need to construct standard and structured data, and encapsulate the processing method code of the XML files. The XML API interfaces are used to obtain the numerical data of different data types in the different quarantine processing systems, and the numerical data of the different data types are subjected to standardized data processing to obtain the standardized quarantine processing data, and data analysis is performed based on the standardized quarantine processing data.

[0028] The data processing method for standardizing the numerical data obtained by the XML API interface includes: encapsulating the identification method of the quarantine commodity category through the XML API interface, which method can be implemented including but not limited to the use of RFID tag list matching. In the XML API interface, a key-value pair list of the corresponding commodity category numerical data is configured as an XML file of standard and structured data. The system will fill in the corresponding XML file according to the key name, where the key name (key) is the quarantine type of the corresponding quarantine commodity, and the value (Value) is the quarantine value of the corresponding quarantine commodity.

[0029] The quarantine commodity category identification method encapsulated by the XML API interface improves the scalability and maintainability of the system. RFID tag list matching technology is used to accurately identify different types of quarantine commodities, and standardized and structured data is stored in XML files by configuring key-value lists. This ensures that every quarantine commodity entering the system can be quickly and accurately classified and assigned a unique identifier.

[0030] When the system receives a new quarantine request, it first determines the quarantine type of the item based on the unique identifier of the item provided in the request and the pre-set identification rules. Then, based on this information, it automatically searches for the corresponding key-value pair list, where the key name represents the specific quarantine item name, and the corresponding value is the specific value or status description under the item. For example, if a piece of goods needs to be tested for temperature sensitivity, the corresponding key may be "Temperature_Sensitivity" and the value may be "High" or "Low".

[0031] In addition, to further ensure data quality, before the original information is filled into the final generated XML document, the data is checked and adjusted as necessary according to a series of preset conversion rules. This can avoid information inconsistency caused by input errors, and also ensure that all output files follow a unified format standard, which is convenient for subsequent data analysis and processing.

[0032] The XML API interface encapsulates the quarantine commodity category identification process, which simplifies the entire operation process and reduces the risk of human intervention. In addition, by introducing a highly customizable key-value pair list mechanism, the system can easily cope with various new demand changes that may arise in the future. Whether adding new quarantine items or modifying existing rules, it can be done by simply updating the relevant configuration files without making large-scale changes to the underlying code, which greatly improves the flexibility and adaptability of the software project.

[0033] The data processing method for standardizing the numerical data obtained by the XML API interface includes: encapsulating a standardized numerical conversion method based on multivariate quarantine data in the XML API interface, specifically including the following steps: obtaining the maximum quarantine data Smax and the minimum quarantine data Smin of the target commodity type according to the key name in the key-Value list of the key-value pair, and calculating the standard deviation σ of different quarantine data S of each commodity type, and performing standardization processing according to the standard deviation according to the following formula: , where M i represents the standardized quarantine data of different quarantine data i corresponding to the commodity type, The average value of the quarantine data of the corresponding commodity type is represented, and the standardized quarantine data Mi of the different quarantine data i of the corresponding commodity type is stored in the key-Value list of the XML API interface. i After that, the standardized quarantine processing data Mi is further integrated and analyzed, and the standardized quarantine processing data M is calculated according to the following formula: i Integrated analysis of: P= , where y i and w i are respectively based on the standardized quarantine processing data M i Corresponding to the pre-quarantine data and post-quarantine data of the commodity type; P represents the integrated analysis result data of the multivariate quarantine data of the same target commodity type, e is the natural constant, and σ is the standard deviation.

[0034] Furthermore, the present invention configures the risk warning level V based on the integrated analysis result data P of the multivariate quarantine data. j, where j is the corresponding level value, and the corresponding risk warning level V is pre-configured j quarantine control strategy, when the integrated analysis result data P of the multivariate quarantine data meets the corresponding risk warning level V j , the corresponding quarantine control strategy will be implemented.

[0035] The quarantine data collection and integration method and system obtain standardized quarantine processing data M i After that, we further obtain the equipment parameters f corresponding to the quarantine process. i and environmental parameters r i , and according to these parameters according to the preset risk warning level V j Perform automatic parameter modulation. Specifically:

[0036] Build an automated parameter modulation model: ,in, are intercept one and intercept two, are regression coefficients one and two, are error term 1 and error term 2; are input variable one and input variable two; Import the preset risk warning level configuration table: Risk Level Level Value Error Term 1 / Error Term 2 <![CDATA[V1]]> 1 0.1 / 0.1 <![CDATA[V2]]> 2 0.11 / 0.11 <![CDATA[V3]]> 3 0.12 / 0.12 Collecting equipment parameters of a preset time length. In this embodiment, the collected equipment parameter data is temperature data. Average temperature data is calculated based on the collected multiple temperature data. The average temperature data is input into the automatic parameter adjustment model as an input variable. The temperature value of the equipment at the next moment is output, and the temperature parameters of the equipment are adjusted according to the temperature data at the next moment. Similarly, multiple environmental parameters within a preset time length are collected, which are environmental humidity data in this embodiment.

[0037] Calculate average humidity data based on multiple environmental humidity data obtained, input the average humidity data into the automatic parameter adjustment model as input variable 2, and output the environmental humidity value at the next moment; According to the corresponding ambient humidity value, adjust the parameters of equipment such as air conditioners or accelerators to make the environmental parameters meet the standards.

[0038] The quarantine treatment parameters are automatically adjusted according to real-time data to ensure that the effect of the quarantine treatment meets the predetermined standards. At the same time, through comprehensive evaluation of data from different dimensions, the effect of the quarantine treatment can be more comprehensively understood, providing more accurate decision support for relevant departments. In addition, this automated parameter modulation also reduces the possibility of human intervention and improves the efficiency and accuracy of quarantine treatment.

[0039] This modulation is to ensure that the final risk alert level can meet quarantine requirements, thereby ensuring the safety of animals, plants, chilled and fresh products.

[0040] Equipment parameters i Including key performance indicators of various quarantine treatment equipment, such as the sensitivity of channel-type radioactive detection equipment, the disinfection efficiency of channel-type outer box spray disinfection equipment, the temperature and humidity control capability of fumigation warehouse equipment, the sterilization effect of high-temperature sterilization equipment for biomedical waste, and the processing capacity of harmless treatment equipment. Environmental parameters r i It involves environmental factors such as temperature, humidity, and air pressure that affect the effectiveness of quarantine treatment.

[0041] Risk warning level V j The value range v is obtained based on the corresponding integrated analysis result data P. A reasonable risk warning threshold range is set based on the historical data and current data analysis results. This range will be evaluated in different dimensions based on the quarantine data of different commodity types i, and a comprehensive evaluation will be performed through weighted summation to obtain quarantine data evaluation results in different dimensions.

[0042] The embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. The embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part, and / or installed from a removable medium. When the computer program is executed by the central processing unit (CPU), the above-mentioned functions defined in the method of the present application are executed. It should be noted that the above-mentioned computer-readable medium of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, a system, device or device of an electrical, magnetic, optical, electromagnetic, infrared segment, or semiconductor, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more wire segments, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, electrical wire, optical cable, RF, etc., or any suitable combination of the foregoing.

[0043] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0044] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the accompanying drawings are only examples and do not limit the present invention. The objectives of the present invention have been fully and effectively achieved. The functional and structural principles of the present invention have been demonstrated and explained in the embodiments. Without departing from the principles, the implementation methods of the present invention may be deformed or modified in any way.

Claims

1. A quarantine data collection and integration method, characterized in that: The method comprises the following steps: Pre-configure the API interface corresponding to the quarantine processing system, determine the commodity type of the target quarantine commodity, and call the API interface corresponding to the quarantine processing system according to the commodity type; Using API interfaces of different quarantine processing systems to obtain quarantine processing data of each quarantined commodity by different quarantine processing systems, wherein the quarantine processing data includes pre-quarantine processing data and post-quarantine processing data; Performing standardized data integration on the quarantine processing data of the different quarantine processing systems to obtain standardized quarantine processing data, and further performing data analysis and calculation on the standardized quarantine processing data; After analysis and calculation, the quarantine data of the corresponding target quarantined commodity before and after quarantine treatment are obtained respectively, and the quarantine data before and after quarantine treatment are further tested and analyzed to determine the quarantine treatment effect of the current target quarantined commodity.

2. A quarantine data collection and integration method according to claim 1, characterized in that: The different quarantine treatment systems include: a channel-type radioactivity detection system, a channel-type outer box spray disinfection system, a fumigation warehouse system, a high-temperature sterilization system for biomedical waste and a harmless treatment system; wherein a highly structured XMLAPI interface is configured for each of the different treatment systems, and the XML API interface is used to obtain numerical data of different data types in the different quarantine treatment systems, and the numerical data of the different data types are subjected to standardized data processing to obtain the standardized quarantine treatment data, and data analysis is performed based on the standardized quarantine treatment data.

3. A quarantine data collection and integration method according to claim 2, characterized in that: The data processing method for standardizing the numerical data obtained by the XML API interface includes: encapsulating a method for identifying the category of quarantined commodities in the XML API interface, and configuring a key-value pair list of numerical data of corresponding commodity categories in the XML API interface, wherein the key name key in the key-value pair is the quarantine type of the corresponding quarantined commodity, and the Value is the quarantine numerical value of the corresponding quarantined commodity, and the key-value pair list encapsulated by the XML API interface is used to construct structured data based on quarantined commodities, wherein a unique identifier is configured for each target quarantined commodity, and the corresponding key-value pair list is called based on the unique identifier and the identified quarantined commodity type, and the corresponding quarantine data is automatically obtained as the key value according to the key name of the key-value pair list.

4. A quarantine data collection and integration method according to claim 3, characterized in that: The data processing method for standardizing the numerical data obtained by the XML API interface includes: encapsulating a standardized numerical conversion method based on multivariate quarantine data in the XML API interface, specifically including the following steps: obtaining the maximum quarantine data S of the target commodity type according to the key name in the key-Value list of the key-value pair; max and minimum quarantine data S min , and calculate the standard deviation σ of different quarantine data S for each commodity type, and perform standardization according to the standard deviation according to the following formula: , where M i represents the standardized quarantine data of different quarantine data i corresponding to the commodity type, represents the average value of the quarantine data of the corresponding commodity type, and the standardized quarantine data M of different quarantine data i of the corresponding commodity type i The key-value list is stored according to the key value of the XML API interface to obtain highly structured and standardized quarantine processing data M i .

5. A quarantine data collection and integration method according to claim 4, characterized in that: After obtaining the standardized quarantine processing data M for the corresponding commodity type i After that, the standardized quarantine processing data M is further processed. i Perform data integration and analysis, and standardize quarantine processing data M according to the following formula i Integrated analysis of: P= , where y i and w i are respectively based on the standardized quarantine processing data M i Corresponding to the pre-quarantine data and post-quarantine data of the commodity type; P represents the integrated analysis result data of the multivariate quarantine data of the same target commodity type, e is the natural constant, and σ is the standard deviation.

6. A quarantine data collection and integration method according to claim 5, characterized in that: Configure risk warning level V based on the integrated analysis result data P of the multi-quarantine data j , where j is the corresponding level value, and the corresponding risk warning level V is pre-configured j quarantine control strategy, when the integrated analysis result data P of the multivariate quarantine data meets the corresponding risk warning level V j , then execute the corresponding quarantine control strategy; Build an automated parameter modulation model: ,in, are intercept one and intercept two, are regression coefficients one and two, are error term 1 and error term 2; are input variable one and input variable two; Import the preset risk warning level configuration table, and determine the values ​​of error one and error two according to the risk warning level configuration table.

7. A quarantine data collection and integration method according to claim 3, characterized in that: Standardized quarantine processing data M of the corresponding commodity type obtained through the XML API interface i After that, obtain the equipment parameters f corresponding to the quarantine process i and environmental parameters r i , and according to the device parameter f i and environmental parameters r i According to the corresponding risk warning level V j Automatic parameter modulation is performed to make the final risk warning level meet the quarantine requirements, wherein the equipment parameter f i Including channel type radioactive detection equipment parameters, channel type outer box spray disinfection equipment parameters, fumigation warehouse equipment parameters, biomedical waste high temperature sterilization equipment parameters, harmless treatment equipment parameters, environmental parameters r i Including temperature, humidity and air pressure.

8. A quarantine data collection and integration method according to claim 7, characterized in that: After completing the corresponding standardized quarantine processing data M i After analysis, the risk warning level V is pre-configured j The numerical range v is obtained based on the corresponding integrated analysis result data P, and the quarantine data i of the corresponding commodity type are evaluated in different dimensions, and a comprehensive evaluation is performed by weighted summation to obtain quarantine data evaluation results of different dimensions.

9. A quarantine data collection and integration system, characterized in that: The system executes a quarantine data collection and integration method as described in any one of claims 1-8 above.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement a quarantine data collection and integration method as described in any one of claims 1 to 8.

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