An information system interface that enables collaborative work

Abstract

The application relates to the technical field of information management, and discloses an information system interface capable of realizing collaborative work, which comprises an external interface, an internal interface, a subsystem module and a control module; the external interface is used for being connected with an external terminal; the internal interface comprises an epidemic situation data synchronization interface, a personnel monitoring data synchronization interface, a personnel information synchronization interface and a nucleic acid detection result synchronization interface, and the internal interface is used for data exchange and communication in the subsystem module; the subsystem module comprises an epidemic situation data acquisition, processing and analysis subsystem, a traceability prevention and control subsystem, an infectious disease knowledge base and an intelligent question and answer subsystem and nucleic acid detection equipment; the control module is connected with the internal interface, the external interface and the subsystem module, and the control module comprises an acquisition unit, a judgment unit and a processing unit. Through the collaborative work of the external interface, the internal interface, the subsystem module and the control module, efficient management and rapid updating of infectious disease related data are realized.

Description

Technical Field

[0001] This invention relates to the field of information management technology, and more specifically, to an information system interface that enables collaborative work. Background Technology

[0002] With the rapid development and continuous progress of information technology, the information-based management of infectious diseases has become increasingly important and indispensable. In today's information age, traditional infectious disease management methods are gradually revealing their limitations, with data silos, poor information sharing, and inadequate real-time performance being particularly prominent issues. These problems make traditional management methods ill-suited to the complexity and urgency of modern infectious disease prevention and control, and unable to efficiently respond to public health emergencies.

[0003] Therefore, it is necessary to design an information system interface that enables collaborative work to solve the problems existing in the current technology, especially when applied to the field of infectious diseases. Summary of the Invention

[0004] In view of this, the present invention proposes an information system interface that enables collaborative work, aiming to address the problem that traditional management methods are difficult to adapt to the complexity and urgency of modern infectious disease prevention and control work, and are unable to efficiently respond to public health emergencies.

[0005] This invention proposes an interface for an information system that enables collaborative work, comprising:

[0006] External interfaces, internal interfaces, subsystem modules, and control modules;

[0007] The external interface is used to connect to an external terminal;

[0008] The internal interfaces include an epidemic data synchronization interface, a personnel monitoring data synchronization interface, a personnel information synchronization interface, and a nucleic acid test result synchronization interface. The internal interfaces are used for data exchange and communication within the subsystem module.

[0009] The subsystem modules include an epidemic data collection, processing and analysis subsystem, a source tracing and prevention subsystem, an infectious disease knowledge base and intelligent question-and-answer subsystem, and nucleic acid testing equipment;

[0010] The control module is connected to the internal interface, the external interface, and the subsystem module. The control module includes a data acquisition unit, a judgment unit, and a processing unit.

[0011] The acquisition unit is configured to acquire the data element feature information transmitted by each of the internal interfaces, and determine the initial transmission strategy of each of the internal interfaces based on the data element feature information.

[0012] The judgment unit is configured to extract corresponding historical transmission records from the historical transmission record library based on the internal interface and the initial transmission strategy, analyze the historical transmission records, calculate the historical transmission deviation coefficient of the internal interface based on the analysis results, and determine whether the initial transmission strategy needs to be adjusted based on the historical transmission deviation coefficient.

[0013] The processing unit is configured to, when it is determined that the initial transmission strategy needs to be adjusted, control the acquisition unit to acquire the upload time and download time of the subsystem module, obtain a transmission adjustment coefficient based on the upload time and download time, and adjust the initial transmission strategy based on the transmission adjustment coefficient.

[0014] Furthermore, the data element feature information includes real-time epidemic data, personnel monitoring data, personnel data, and nucleic acid test data;

[0015] The epidemic data collection, processing and analysis subsystem sends the real-time epidemic data to the source tracing and prevention subsystem through the epidemic data synchronization interface;

[0016] The infectious disease knowledge base and intelligent question-and-answer subsystem send the personnel monitoring data to the source tracing and prevention subsystem through the personnel monitoring data synchronization interface;

[0017] The source tracing and prevention subsystem sends the personnel data to the infectious disease knowledge base and intelligent question-and-answer subsystem through the personnel information synchronization interface;

[0018] The nucleic acid testing equipment sends the nucleic acid testing data to the source tracing and prevention subsystem through the nucleic acid testing result synchronization interface.

[0019] Further, when determining the initial transmission strategy for each of the internal interfaces based on the data element feature information, the process includes:

[0020] When the data element feature information is the real-time epidemic data, the initial transmission strategy of the epidemic data synchronization interface is determined to be the first transmission strategy;

[0021] When the data element feature information is personnel monitoring data, the initial transmission strategy of the personnel monitoring data synchronization interface is determined to be the second transmission strategy;

[0022] When the data element feature information is personnel data, the initial transmission strategy of the personnel information synchronization interface is determined to be the third transmission strategy;

[0023] When the data element feature information is nucleic acid detection data, the initial transmission strategy of the nucleic acid detection result synchronization interface is determined to be the fourth transmission strategy.

[0024] Furthermore, when analyzing the historical transmission records and calculating the historical transmission deviation coefficient of the internal interface based on the analysis results, the process includes:

[0025] The historical transmission records are analyzed to identify normal and abnormal transmission behaviors.

[0026] Identify the abnormal impact factors corresponding to each abnormal transmission behavior and construct an abnormal impact factor sequence;

[0027] The frequency of occurrence of the aforementioned normal transmission behavior is statistically analyzed and denoted as the normal frequency.

[0028] The frequency of occurrence of the aforementioned abnormal transmission behavior is statistically analyzed and denoted as the abnormal frequency;

[0029] The historical transmission deviation coefficient of the internal interface is calculated based on the abnormal influence factor sequence, normal frequency, and abnormal frequency.

[0030] Furthermore, the historical transmission deviation coefficient is obtained by the following formula:

[0031] ;

[0032] Where D represents the historical transmission deviation coefficient; E i F represents the anomalous influence factor of the i-th anomalous transmission behavior. i N represents the influence coefficient of the i-th abnormal transmission behavior; N1 represents the normal frequency; N2 represents the abnormal frequency; M represents the total number of abnormal transmission behaviors.

[0033] Furthermore, when determining the abnormal influence factor corresponding to each abnormal transmission behavior, the following are included:

[0034] Extract the actual transmission time corresponding to each abnormal transmission behavior, obtain the standard transmission time, and calculate the first transmission time difference based on the actual transmission time and the standard transmission time.

[0035] Analyze all the normal transmission behaviors to determine the transmission time corresponding to each normal transmission behavior, and extract the maximum transmission time;

[0036] Calculate the second transmission time difference based on the actual transmission time and the maximum transmission time;

[0037] Calculate the abnormal impact factor corresponding to each of the abnormal transmission behaviors based on the first transmission time difference and the second transmission time difference;

[0038] The abnormal influence factor is obtained by the following formula:

[0039] ;

[0040] Among them, Ej ΔT1 represents the abnormal influence factor corresponding to the j-th abnormal transmission behavior; ΔT2 represents the first transmission time difference; α represents the first adjustment coefficient; β represents the second adjustment coefficient.

[0041] Furthermore, when determining whether the initial transmission strategy needs to be adjusted based on the historical transmission deviation coefficient, the following steps are included:

[0042] The historical transmission deviation coefficient is compared with the historical transmission deviation coefficient threshold, and the result of the comparison determines whether the initial transmission strategy needs to be adjusted.

[0043] When the historical transmission deviation coefficient is greater than or equal to the historical transmission deviation coefficient threshold, it is determined that the initial transmission strategy needs to be adjusted.

[0044] When the historical transmission deviation coefficient is less than the historical transmission deviation coefficient threshold, it is determined that no adjustment to the initial transmission strategy is required.

[0045] Further, when adjusting the initial transmission strategy based on the upload time and download time, a transmission adjustment coefficient is obtained, and the initial transmission strategy is adjusted based on the transmission adjustment coefficient, the following steps are included:

[0046] Obtain the ideal upload time, and calculate the upload time ratio based on the ideal upload time and the ideal upload time.

[0047] Obtain the ideal download time, and calculate the download time ratio based on the actual download time and the ideal download time;

[0048] The transmission status value is obtained by taking a weighted average of the upload time ratio and the download time ratio.

[0049] The transmission status value is compared with historical data, and the transmission adjustment coefficient is determined based on the comparison result;

[0050] When there is a historical transmission status value in the historical data that is the same as the transmission status value, the initial transmission strategy is adjusted according to the historical transmission adjustment coefficient corresponding to the historical transmission status value.

[0051] When there is no historical transmission status value in the historical data that is the same as the transmission status value, the maximum correlation index between the transmission status value and the historical data is calculated, and the initial transmission strategy is adjusted according to the maximum correlation index.

[0052] Further, when adjusting the initial transmission strategy based on the maximum correlation index, the following steps are included:

[0053] A transmission adjustment coefficient range is defined, wherein the transmission adjustment coefficient range includes a first transmission adjustment coefficient, a second transmission adjustment coefficient, and a third transmission adjustment coefficient;

[0054] Calculate the ratio of the maximum correlation index to the maximum correlation index threshold;

[0055] When the exponent ratio is greater than 1 and less than or equal to 1.2, the first transmission adjustment coefficient is selected to adjust the initial transmission strategy.

[0056] When the exponent ratio is greater than 1.2 and less than or equal to 1.4, the second transmission adjustment coefficient is selected to adjust the initial transmission strategy.

[0057] When the exponent ratio is greater than 1.4, the third transmission adjustment coefficient is selected to adjust the initial transmission strategy.

[0058] Furthermore, the maximum correlation index is obtained by the following formula:

[0059] ;

[0060] Among them, C max ω represents the maximum correlation index; k R represents the weight of the k-th historical transmission state value in the historical data; k This represents the k-th historical transmission status value in the historical data; n represents the total number of historical transmission status values ​​in the historical data.

[0061] Compared with existing technologies, the beneficial effects of this invention are as follows: The collaborative information system interface provided by this invention achieves efficient management and rapid updating of infectious disease-related data through the collaborative work of external interfaces, internal interfaces, subsystem modules, and control modules; the collaborative information system interface provided by this invention can quickly respond to changes in the epidemic situation, thereby providing accurate and timely data support for public health decision-making; through the optimization of processing units, the system can automatically adjust data transmission strategies to ensure the rapid flow of key information while reducing unnecessary data transmission and improving the overall system operating efficiency; the collaborative information system interface provided by this invention aims to provide a reliable, efficient, and intelligent information platform for the prevention, control, and management of infectious diseases. Attached Figure Description

[0062] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0063] Figure 1 This invention provides a structural block diagram of an information system interface that enables collaborative work in embodiments of the invention. Detailed Implementation

[0064] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0065] See Figure 1 As shown in some embodiments of this application, this embodiment provides an information system interface that enables collaborative work, including:

[0066] External interfaces, internal interfaces, subsystem modules, and control modules;

[0067] The external interface is used to connect to an external terminal;

[0068] The internal interfaces include an epidemic data synchronization interface, a personnel monitoring data synchronization interface, a personnel information synchronization interface, and a nucleic acid test result synchronization interface. The internal interfaces are used for data exchange and communication within the subsystem module.

[0069] The subsystem modules include an epidemic data collection, processing and analysis subsystem, a source tracing and prevention subsystem, an infectious disease knowledge base and intelligent question-and-answer subsystem, and nucleic acid testing equipment;

[0070] The control module is connected to the internal interface, the external interface, and the subsystem module. The control module includes a data acquisition unit, a judgment unit, and a processing unit.

[0071] The acquisition unit is configured to acquire the data element feature information transmitted by each of the internal interfaces, and determine the initial transmission strategy of each of the internal interfaces based on the data element feature information.

[0072] The judgment unit is configured to extract corresponding historical transmission records from the historical transmission record library based on the internal interface and the initial transmission strategy, analyze the historical transmission records, calculate the historical transmission deviation coefficient of the internal interface based on the analysis results, and determine whether the initial transmission strategy needs to be adjusted based on the historical transmission deviation coefficient.

[0073] The processing unit is configured to, when it is determined that the initial transmission strategy needs to be adjusted, control the acquisition unit to acquire the upload time and download time of the subsystem module, obtain a transmission adjustment coefficient based on the upload time and download time, and adjust the initial transmission strategy based on the transmission adjustment coefficient.

[0074] As can be seen, the collaborative information system interface provided in this embodiment achieves efficient management and rapid updating of infectious disease-related data through the collaborative work of external interfaces, internal interfaces, subsystem modules, and control modules. This collaborative information system interface can quickly respond to changes in the epidemic situation, thereby providing accurate and timely data support for public health decision-making. Through optimization of the processing unit, the system can automatically adjust data transmission strategies to ensure the rapid flow of key information while reducing unnecessary data transmission and improving the overall system operating efficiency. The collaborative information system interface provided in this embodiment aims to provide a reliable, efficient, and intelligent information platform for the prevention, control, and management of infectious diseases.

[0075] In this embodiment, Table 1 is the system management internal interface identifier table:

[0076] Table 1

[0077]

[0078] In this embodiment, Table 2 shows the data element characteristic information transmitted by the epidemic data synchronization interface:

[0079] Table 2

[0080]

[0081] In this embodiment, Table 3 is the personnel monitoring data interface identifier table:

[0082] Table 3

[0083]

[0084] In this embodiment, Table 4 shows the data element characteristic information transmitted by the personnel monitoring data synchronization interface—monitoring records:

[0085] Table 4

[0086]

[0087] Table 5 shows the data element characteristic information transmitted by the personnel monitoring data synchronization interface—close contact personnel records:

[0088] Table 5

[0089]

[0090] Table 6 shows the characteristic information of data elements transmitted by the personnel monitoring data synchronization interface—activity trajectory records:

[0091] Table 6

[0092]

[0093] Table 7 shows the characteristic information of data elements transmitted through the personnel monitoring data synchronization interface—epidemiological survey records:

[0094] Table 7

[0095]

[0096] In this embodiment, Table 8 is the personnel information synchronization interface identifier table:

[0097] Table 8

[0098]

[0099] In this embodiment, Table 9 shows the data element characteristic information transmitted by the personnel information synchronization interface:

[0100] Table 9

[0101]

[0102] In this embodiment, Table 10 is the nucleic acid testing data synchronization interface identifier table:

[0103] Table 10

[0104]

[0105] In this embodiment, Table 11 shows the data element characteristic information transmitted by the nucleic acid detection data synchronization interface:

[0106] Table 11

[0107]

[0108] It is understood that this embodiment provides detailed interface usage instructions and data element characteristic information to ensure that users can quickly understand and correctly use the system interfaces. Through this information, users can clearly understand the function, priority, sender, and receiver of each interface, thereby effectively synchronizing data and exchanging information.

[0109] Specifically, the data element feature information includes real-time epidemic data, personnel monitoring data, personnel data, and nucleic acid test data;

[0110] The epidemic data collection, processing and analysis subsystem sends the real-time epidemic data to the source tracing and prevention subsystem through the epidemic data synchronization interface;

[0111] The infectious disease knowledge base and intelligent question-and-answer subsystem send the personnel monitoring data to the source tracing and prevention subsystem through the personnel monitoring data synchronization interface;

[0112] The source tracing and prevention subsystem sends the personnel data to the infectious disease knowledge base and intelligent question-and-answer subsystem through the personnel information synchronization interface;

[0113] The nucleic acid testing equipment sends the nucleic acid testing data to the source tracing and prevention subsystem through the nucleic acid testing result synchronization interface.

[0114] It can be seen that when the epidemic data collection, processing, and analysis subsystem receives real-time epidemic data, it transmits the data to the source tracing and prevention subsystem via the epidemic data synchronization interface. Upon receiving this data, the source tracing and prevention subsystem can quickly analyze the transmission path and potential risks of the epidemic, thereby formulating corresponding prevention and control measures. The infectious disease knowledge base and intelligent question-and-answer subsystem can provide the public with accurate epidemic information and protection suggestions based on real-time epidemic data, reducing public panic and improving the popularization of epidemic prevention knowledge. Nucleic acid testing equipment updates test results to the system in real time through the nucleic acid test result synchronization interface, ensuring the timeliness and accuracy of the data. Through such information system interfaces, more refined monitoring and management of infectious disease epidemics can be achieved, providing solid technical support for public health security.

[0115] Specifically, determining the initial transmission strategy for each of the internal interfaces based on the data element feature information includes:

[0116] When the data element feature information is the real-time epidemic data, the initial transmission strategy of the epidemic data synchronization interface is determined to be the first transmission strategy;

[0117] When the data element feature information is personnel monitoring data, the initial transmission strategy of the personnel monitoring data synchronization interface is determined to be the second transmission strategy;

[0118] When the data element feature information is personnel data, the initial transmission strategy of the personnel information synchronization interface is determined to be the third transmission strategy;

[0119] When the data element feature information is nucleic acid detection data, the initial transmission strategy of the nucleic acid detection result synchronization interface is determined to be the fourth transmission strategy.

[0120] It is understood that the first, second, third, and fourth transmission strategies correspond to different data transmission priorities and frequencies. In this embodiment, the first transmission strategy has a data transmission priority of 3 and a preferred transmission frequency of once per minute to ensure that the latest developments in the epidemic can be quickly captured and processed; the second transmission strategy has a priority of 3 and a preferred transmission frequency of once per hour to ensure timely updates of personnel monitoring data; the third transmission strategy has a priority of 2 and a preferred transmission frequency of once per day to meet the regular update needs of personnel data; and the fourth transmission strategy has a priority of 2 and a preferred transmission frequency of updating after each batch of tests to ensure the accuracy and timeliness of nucleic acid test results. Through this hierarchical transmission strategy, the system can rationally allocate resources according to the importance and urgency of the data, optimize data transmission efficiency, and avoid unnecessary network congestion and data redundancy.

[0121] Specifically, when analyzing the historical transmission records and calculating the historical transmission deviation coefficient of the internal interface based on the analysis results, the process includes:

[0122] The historical transmission records are analyzed to identify normal and abnormal transmission behaviors.

[0123] Identify the abnormal impact factors corresponding to each abnormal transmission behavior and construct an abnormal impact factor sequence;

[0124] The frequency of occurrence of the aforementioned normal transmission behavior is statistically analyzed and denoted as the normal frequency.

[0125] The frequency of occurrence of the aforementioned abnormal transmission behavior is statistically analyzed and denoted as the abnormal frequency;

[0126] The historical transmission deviation coefficient of the internal interface is calculated based on the abnormal influence factor sequence, normal frequency, and abnormal frequency.

[0127] Specifically, the historical transmission deviation coefficient is obtained by the following formula:

[0128] ;

[0129] Where D represents the historical transmission deviation coefficient; E i F represents the anomalous influence factor of the i-th anomalous transmission behavior. i N represents the influence coefficient of the i-th abnormal transmission behavior; N1 represents the normal frequency; N2 represents the abnormal frequency; M represents the total number of abnormal transmission behaviors.

[0130] Understandably, the construction of the anomaly impact factor sequence is based on anomalies in historical data, including data loss, transmission delays, or data corruption. By analyzing these anomalies, the system can identify key factors affecting data transmission stability and adjust transmission strategies accordingly to reduce the likelihood of similar anomalies in the future. When calculating historical transmission deviation coefficients, the system considers both the frequency of normal transmission behavior and the frequency of abnormal transmission behavior. Normal frequency reflects the normal state of data transmission without anomalies, while abnormal frequency reveals the frequency of anomalies occurring within a specific timeframe. By comparing normal and abnormal frequencies, the system can assess the reliability of the current transmission strategy and adjust accordingly to improve data transmission stability and accuracy. Furthermore, the system also adjusts historical transmission deviation coefficients based on the anomaly impact factor sequence. This sequence, constructed from anomalies recorded in historical data, reflects the severity of different anomalies' impact on data transmission. By incorporating these impact factors into the calculation, the system can more accurately assess the degree of deviation in historical transmissions and optimize transmission strategies accordingly.

[0131] It is understood that the collaborative information system interface provided in this embodiment ensures high efficiency and reliability of data transmission through precise data analysis and transmission strategy adjustments. This intelligent interface design not only enables rapid response to changes in the epidemic situation but also provides timely and accurate data support for public health decision-making, thus playing a vital role in the prevention, control, and management of infectious diseases.

[0132] Specifically, when determining the abnormal impact factor corresponding to each abnormal transmission behavior, the following are included:

[0133] Extract the actual transmission time corresponding to each abnormal transmission behavior, obtain the standard transmission time, and calculate the first transmission time difference based on the actual transmission time and the standard transmission time.

[0134] Analyze all the normal transmission behaviors to determine the transmission time corresponding to each normal transmission behavior, and extract the maximum transmission time;

[0135] Calculate the second transmission time difference based on the actual transmission time and the maximum transmission time;

[0136] Calculate the abnormal impact factor corresponding to each of the abnormal transmission behaviors based on the first transmission time difference and the second transmission time difference;

[0137] The abnormal influence factor is obtained by the following formula:

[0138] ;

[0139] Among them, E jΔT1 represents the abnormal influence factor corresponding to the j-th abnormal transmission behavior; ΔT2 represents the first transmission time difference; α represents the first adjustment coefficient; β represents the second adjustment coefficient.

[0140] Understandably, the first adjustment coefficient α and the second adjustment coefficient β are parameters pre-set based on the actual application scenario and data transmission requirements, used to adjust the calculation results of the anomaly impact factor. The value of α is typically less than 1, used to reduce the impact of the first transmission time difference ΔT1 on the anomaly impact factor E. j The influence of β is to avoid over-adjustment due to individual abnormal transmission behaviors; and the value of β is usually greater than 1, used to amplify the effect of the second transmission time difference ΔT2 on the abnormal influence factor E. j The impact of anomalies is mitigated to ensure that when transmission time significantly exceeds the normal range, the anomaly impact factor accurately reflects the degree of transmission anomaly. By appropriately setting the values ​​of α and β, the system can balance the impact of anomalies on transmission strategy adjustments, ensuring sensitivity to anomalies while avoiding overreaction, thereby achieving more accurate and stable transmission strategy optimization. In practical applications, the values ​​of α and β need to be adjusted according to the specific performance of the system and the real-time requirements of data transmission to achieve the best system operating effect.

[0141] Specifically, when determining whether the initial transmission strategy needs adjustment based on the historical transmission deviation coefficient, the following steps are included:

[0142] The historical transmission deviation coefficient is compared with the historical transmission deviation coefficient threshold, and the result of the comparison determines whether the initial transmission strategy needs to be adjusted.

[0143] When the historical transmission deviation coefficient is greater than or equal to the historical transmission deviation coefficient threshold, it is determined that the initial transmission strategy needs to be adjusted.

[0144] When the historical transmission deviation coefficient is less than the historical transmission deviation coefficient threshold, it is determined that no adjustment to the initial transmission strategy is required.

[0145] Understandably, the historical transmission deviation coefficient threshold is a pre-set reference value based on system performance and data transmission requirements, used to assess whether the current transmission strategy needs optimization. When the historical transmission deviation coefficient exceeds this threshold, it means that the current transmission strategy may not meet the stability and efficiency requirements of data transmission, thus requiring adjustment. The purpose of adjustment is to reduce the occurrence of abnormal transmission behavior and improve the accuracy and timeliness of data transmission. In practice, the system dynamically adjusts the transmission strategy based on the magnitude and trend of the historical transmission deviation coefficient to adapt to the needs of changing epidemic data. For example, if the system detects that the historical transmission deviation coefficient of the epidemic data synchronization interface continues to rise, it indicates that the transmission strategy of that interface may need optimization to ensure that epidemic data can be synchronized to various subsystems more quickly and accurately. Through such a dynamic adjustment mechanism, the interfaces of collaborative information systems can respond more flexibly to changes in the epidemic, providing stronger technical support for public health security.

[0146] Specifically, when obtaining a transmission adjustment coefficient based on the upload time and download time, and adjusting the initial transmission strategy based on the transmission adjustment coefficient, the following steps are included:

[0147] Obtain the ideal upload time, and calculate the upload time ratio based on the ideal upload time and the ideal upload time.

[0148] Obtain the ideal download time, and calculate the download time ratio based on the actual download time and the ideal download time;

[0149] The transmission status value is obtained by taking a weighted average of the upload time ratio and the download time ratio.

[0150] The transmission status value is compared with historical data, and the transmission adjustment coefficient is determined based on the comparison result;

[0151] When there is a historical transmission status value in the historical data that is the same as the transmission status value, the initial transmission strategy is adjusted according to the historical transmission adjustment coefficient corresponding to the historical transmission status value.

[0152] When there is no historical transmission status value in the historical data that is the same as the transmission status value, the maximum correlation index between the transmission status value and the historical data is calculated, and the initial transmission strategy is adjusted according to the maximum correlation index.

[0153] Understandably, ideal upload and download times are parameters preset based on system load and network conditions, representing the ideal time window for data transmission. By calculating the ratio of upload and download times to the ideal times, the efficiency and timeliness of current data transmission can be assessed. The transmission status value is obtained by weighted averaging the upload and download time ratios, comprehensively reflecting the overall performance of data upload and download. When comparing the transmission status value with historical data, if identical historical transmission status values ​​exist, the corresponding historical transmission adjustment coefficient can be directly used to adjust the initial transmission strategy. If identical historical transmission status values ​​do not exist, the maximum correlation index between the transmission status value and historical data needs to be calculated to determine the most appropriate adjustment coefficient. This dynamic adjustment mechanism ensures that the system can flexibly adjust the transmission strategy based on real-time data transmission conditions, thereby optimizing overall system performance and response speed. In this way, collaborative information system interfaces can process epidemic data more efficiently, providing more reliable data support for public health decision-making.

[0154] Specifically, adjusting the initial transmission strategy based on the maximum correlation index includes:

[0155] A transmission adjustment coefficient range is defined, wherein the transmission adjustment coefficient range includes a first transmission adjustment coefficient, a second transmission adjustment coefficient, and a third transmission adjustment coefficient;

[0156] Calculate the ratio of the maximum correlation index to the maximum correlation index threshold;

[0157] When the exponent ratio is greater than 1 and less than or equal to 1.2, the first transmission adjustment coefficient is selected to adjust the initial transmission strategy.

[0158] When the exponent ratio is greater than 1.2 and less than or equal to 1.4, the second transmission adjustment coefficient is selected to adjust the initial transmission strategy.

[0159] When the exponent ratio is greater than 1.4, the third transmission adjustment coefficient is selected to adjust the initial transmission strategy.

[0160] Understandably, the transmission adjustment coefficient range is pre-set based on the actual system operation and data transmission needs, providing a flexible range for adjusting the initial transmission strategy. The first, second, and third transmission adjustment coefficients correspond to different levels of adjustment to adapt to different data transmission anomalies. By setting such a range, the system can select the most appropriate adjustment coefficient for strategy adjustment based on the ratio of the maximum correlation index to its threshold. For example, when the index ratio is between 1 and 1.2, the first transmission adjustment coefficient is selected for fine-tuning to address minor transmission deviations; when the index ratio is between 1.2 and 1.4, the second transmission adjustment coefficient is selected for moderate adjustments to address moderate transmission deviations; and when the index ratio exceeds 1.4, the third transmission adjustment coefficient is selected for significant adjustments to address severe transmission deviations. This tiered adjustment mechanism ensures that the system can respond appropriately to different transmission problems, thereby guaranteeing the stability and reliability of data transmission. In this way, collaborative information system interfaces can more intelligently adapt to various data transmission challenges, providing stronger technical support for public health security.

[0161] Specifically, the maximum correlation index is obtained by the following formula:

[0162] ;

[0163] Among them, C max ω represents the maximum correlation index; k R represents the weight of the k-th historical transmission state value in the historical data; k This represents the k-th historical transmission status value in the historical data; n represents the total number of historical transmission status values ​​in the historical data.

[0164] It is understandable that each historical transmission state value in the historical data corresponds to a weight ω. k This weight reflects the importance or frequency of the state value in historical data. Weight ω k The determination of is usually based on statistical analysis of historical data to ensure that more frequent or more important historical state values ​​have a greater impact on the results when calculating the maximum correlation index. kThis represents the k-th historical transmission state value in the historical data, which is compared with the current transmission state value to determine the correlation between the two. n represents the total number of historical transmission state values ​​in the historical data, ensuring that all historical state values ​​are considered when calculating the maximum correlation index. In this way, the system can comprehensively consider the diversity and complexity of historical data, thereby more accurately assessing the correlation between the current transmission state and historical data, providing a scientific basis for adjusting the initial transmission strategy. This correlation analysis method based on historical data enables the interfaces of collaborative information systems to more intelligently identify and respond to abnormal patterns in data transmission, thereby improving the stability and efficiency of the entire system.

[0165] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0166] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0167] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0168] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0169] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An interface for information systems that can work in cooperation, characterized in that, The system comprises an external interface, an internal interface, a subsystem module and a control module. The external interface is used to connect with an external terminal. The internal interface comprises an epidemic data synchronization interface, a personnel monitoring data synchronization interface, a personnel information synchronization interface and a nucleic acid detection result synchronization interface, and is used for data exchange and communication within the subsystem module. The subsystem module comprises an epidemic data acquisition, processing and analysis subsystem, a traceability prevention and control subsystem, an infectious disease knowledge base and an intelligent question and answer subsystem, and a nucleic acid detection device. The control module is connected with the internal interface, the external interface and the subsystem module, and comprises an acquisition unit, a judgment unit and a processing unit. The acquisition unit is configured to acquire data element characteristic information transmitted by each internal interface, and determine an initial transmission strategy of each internal interface according to the data element characteristic information. The judgment unit is configured to extract corresponding historical transmission records from a historical transmission record library based on the internal interface and the initial transmission strategy, analyze the historical transmission records, and calculate a historical transmission deviation coefficient of the internal interface based on the analysis result. Whether the initial transmission strategy needs to be adjusted is determined according to the historical transmission deviation coefficient. The processing unit is configured to control the acquisition unit to acquire upload time and download time of the subsystem module when it is determined that the initial transmission strategy needs to be adjusted, obtain a transmission adjustment coefficient according to the upload time and the download time, and adjust the initial transmission strategy according to the transmission adjustment coefficient. When the upload time and the download time are obtained to adjust the initial transmission strategy according to the transmission adjustment coefficient, it comprises: An ideal upload time is obtained, and an upload time ratio is calculated according to the upload time and the ideal upload time. An ideal download time is obtained, and a download time ratio is calculated according to the download time and the ideal download time. The upload time ratio and the download time ratio are weighted and averaged to obtain a transmission state value. The transmission state value is compared with historical data, and the transmission adjustment coefficient is determined according to the comparison result. When there is a historical transmission state value same as the transmission state value in the historical data, the initial transmission strategy is adjusted according to the historical transmission adjustment coefficient corresponding to the historical transmission state value. When there is no historical transmission state value same as the transmission state value in the historical data, a maximum correlation index of the transmission state value and the historical data is calculated, and the initial transmission strategy is adjusted according to the maximum correlation index. When the initial transmission strategy is adjusted according to the maximum correlation index, it comprises: A transmission adjustment coefficient interval is set, wherein the transmission adjustment coefficient interval comprises a first transmission adjustment coefficient, a second transmission adjustment coefficient and a third transmission adjustment coefficient. An index ratio of the maximum correlation index and a maximum correlation index threshold value is calculated. When the index ratio is greater than 1 and less than or equal to 1.2, the first transmission adjustment coefficient is selected to adjust the initial transmission strategy. ​ When the exponential ratio is greater than 1.2 and less than or equal to 1.4, the second transmission adjustment coefficient is selected to adjust the initial transmission strategy; When the exponential ratio is greater than 1.4, the third transmission adjustment coefficient is selected to adjust the initial transmission strategy.

2. The interoperable information system interface of claim 1, wherein, The data element characteristic information includes real-time epidemic data, personnel monitoring data, personnel data, and nucleic acid detection data; The epidemic data acquisition, processing, and analysis subsystem sends the real-time epidemic data to the traceability prevention and control subsystem through the epidemic data synchronization interface; The infectious disease knowledge base and intelligent question and answer subsystem sends the personnel monitoring data to the traceability prevention and control subsystem through the personnel monitoring data synchronization interface; The traceability prevention and control subsystem sends the personnel data to the infectious disease knowledge base and intelligent question and answer subsystem through the personnel information synchronization interface; The nucleic acid detection device sends the nucleic acid detection data to the traceability prevention and control subsystem through the nucleic acid detection result synchronization interface.

3. The interoperable information system interface of claim 2, wherein, When determining the initial transmission strategy of each internal interface according to the data element characteristic information, the following steps are included: When the data element characteristic information is the real-time epidemic data, the initial transmission strategy of the epidemic data synchronization interface is determined to be the first transmission strategy; When the data element characteristic information is the personnel monitoring data, the initial transmission strategy of the personnel monitoring data synchronization interface is determined to be the second transmission strategy; When the data element characteristic information is the personnel data, the initial transmission strategy of the personnel information synchronization interface is determined to be the third transmission strategy; When the data element characteristic information is the nucleic acid detection data, the initial transmission strategy of the nucleic acid detection result synchronization interface is determined to be the fourth transmission strategy.

4. The interoperable information technology system interface of claim 1, wherein, When analyzing the historical transmission records and calculating the historical transmission deviation coefficient of the internal interface based on the analysis result, the following steps are included: Analyze the historical transmission records to obtain normal transmission behaviors and abnormal transmission behaviors; Determine the abnormal influence factor corresponding to each abnormal transmission behavior and construct an abnormal influence factor sequence; Statistically record the frequency of the normal transmission behaviors as normal frequency; Statistically record the frequency of the abnormal transmission behaviors as abnormal frequency; Calculate the historical transmission deviation coefficient of the internal interface according to the abnormal influence factor sequence, the normal frequency, and the abnormal frequency.

5. The information system interface of claim 4, wherein, The historical transmission deviation coefficient is obtained by the following formula: ； Wherein, D represents the historical transmission deviation coefficient; E i represents the abnormal influence factor of the i th abnormal transmission behavior, F i represents the influence coefficient of the i th abnormal transmission behavior; N1 represents the normal frequency; N2 represents the abnormal frequency; and M represents the total number of abnormal transmission behaviors.

6. The interoperable information technology system interface of claim 4, wherein, When determining the abnormal influence factor corresponding to each abnormal transmission behavior, the following steps are included: Extract the actual transmission time corresponding to each abnormal transmission behavior, obtain the standard transmission time, and calculate the first transmission time difference value according to the actual transmission time and the standard transmission time; Analyze all the normal transmission behaviors, determine the transmission time corresponding to each normal transmission behavior, and extract the maximum transmission time; Calculate the second transmission time difference value according to the actual transmission time and the maximum transmission time; Calculate the abnormal influence factor corresponding to each abnormal transmission behavior based on the first transmission time difference value and the second transmission time difference value; The abnormal influence factor is obtained by the following formula: ； wherein E j represents the abnormal influence factor corresponding to the jth abnormal transmission behavior; ΔT1 represents the first transmission time difference value; ΔT2 represents the second transmission time difference value; α represents the first adjustment coefficient; and β represents the second adjustment coefficient.

7. The interoperable information technology system interface of claim 1, wherein, When judging whether the initial transmission strategy needs to be adjusted according to the historical transmission deviation coefficient, comprising: comparing the historical transmission deviation coefficient with a historical transmission deviation coefficient threshold value, and judging whether the initial transmission strategy needs to be adjusted according to the comparison result; when the historical transmission deviation coefficient is greater than or equal to the historical transmission deviation coefficient threshold value, it is determined that the initial transmission strategy needs to be adjusted; when the historical transmission deviation coefficient is less than the historical transmission deviation coefficient threshold value, it is determined that the initial transmission strategy does not need to be adjusted.

8. The interoperable information system interface of claim 7, wherein, The maximum correlation index is obtained by the following formula: ； wherein C max represents the maximum correlation index; ω k represents the weight of the kth historical transmission state value in the historical data; R k represents the kth historical transmission state value in the historical data; and n represents the total number of historical transmission state values in the historical data.

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