Test data processing method, device, test system, electronic equipment and medium

Abstract

The present disclosure relates to a test data processing method, device, test system, electronic device and medium. The test data processing method includes obtaining the test data of each test user, the test data of each test user is the test data corresponding to the test device worn by each test user, and the evaluation data corresponding to each test user is determined according to the test data of each test user. The evaluation data corresponding to each test user includes the risk baseline score corresponding to the test user and the infection risk score corresponding to each test user associated with the test user. The test results are obtained according to the evaluation data corresponding to all test users. Through the above method, the test data of each test user is obtained, and the test data of all users are analyzed to obtain the overall test results for the epidemic prevention system, so as to clarify the deficiencies of the existing epidemic prevention system, so as to optimize the existing epidemic prevention system according to the test results.

Description

Technical Field

[0001] The present disclosure relates to the field of testing technology, and in particular, to a test data processing method, device, test system, electronic equipment and medium. Background Art

[0002] For urban rail transit that serves the public, the subsystems for passenger services and operation and maintenance services management have designed and developed epidemic prevention-related functional modules. These epidemic prevention-related functional modules are used for multimedia epidemic prevention information reminders, broadcast information epidemic prevention reminders, passenger distance control, and detection of whether passengers are wearing masks correctly and continuously.

[0003] In the related technologies, the testing and verification technologies are all for testing and verification of their individual functions. Verify whether there are prompts for broadcast information. Verify whether the system has alarm prompts when the distance between passengers is too small or the masks are not worn correctly. It is impossible to optimize the existing epidemic prevention system based on these prompts in the testing and verification methods. Summary of the invention

[0004] The purpose of the present disclosure is to provide a test data processing method, device, test system, electronic device and medium, which obtains the test data of each test user and analyzes the test data of all users to obtain the overall test results, so as to optimize the existing epidemic prevention system according to the test results.

[0005] In order to achieve the above object, according to a first aspect of an embodiment of the present disclosure, a test data processing method is provided, which is applied to a test application server, and the method includes:

[0006] Acquire test data of each test user, where the test data of each test user is test data corresponding to the test device worn by each test user;

[0007] Determine the evaluation data corresponding to each test user according to the test data of each test user, wherein the evaluation data corresponding to each test user includes the risk baseline score corresponding to the test user and the infection risk score corresponding to each test user associated with the test user;

[0008] The test results are obtained based on the evaluation data corresponding to all test users.

[0009] Optionally, the test data includes the duration and facial monitoring results of any two test users detected in each relative distance range;

[0010] Determining the evaluation data corresponding to each test user according to the test data of each test user includes:

[0011] According to the duration of any two test users in each relative distance range, determine the test group where the infectious behavior occurs, and each test group contains two test users;

[0012] Determine the total infection risk score between the two test users in each test group based on the duration and facial monitoring results of any two test users in each relative distance range;

[0013] Based on the total infection risk score of all test groups, the evaluation data corresponding to each test user is determined.

[0014] Optionally, determining the test group where the infectious behavior occurs according to the duration of any two test users in each relative distance range includes:

[0015] For any two test users, determine the duration during which the relative distance between the two test users is less than the infectious distance based on the duration during which the two test users are in each relative distance range;

[0016] When the relative distance between the arbitrary two test users is less than the infectious distance for a duration greater than the infectious time, the arbitrary two test users are determined as a test group in which infectious behavior occurs.

[0017] Optionally, the facial monitoring result includes the orientation of the test device and the facial image of the test user;

[0018] Determining the total infection risk score between the two test users in each test group according to the duration and facial monitoring results of any two test users in each relative distance range includes:

[0019] Determine the mask wearing status and relative facial angle of any two test users in each relative distance range according to the orientation of the test device and the facial images of the test users;

[0020] The duration, mask wearing status and relative facial angle of any two test users within the infectious distance are obtained respectively in each relative distance range, and multiple groups of test data corresponding to any two test users are obtained;

[0021] According to each set of test data, the infectious risk sub-score corresponding to the set of test data is calculated;

[0022] The infection risk sub-scores corresponding to multiple groups of test data corresponding to any two test users are summed up to obtain the total infection risk score between the two test users included in each test group.

[0023] Optionally, based on the total infection risk score of all test groups, the evaluation data corresponding to each test user is determined, including:

[0024] Based on the order in which the infectious behaviors of the test groups occur and according to the total infection risk score of each test group, the infection data of the test users included in each test group are updated in sequence to obtain the evaluation data corresponding to each test user.

[0025] Optionally, the test results include overall infectivity;

[0026] The test results are obtained according to the evaluation data corresponding to all test users, including:

[0027] According to the evaluation data corresponding to all test users, the maximum infection risk base and the sum of actual infection risks of all test users are obtained;

[0028] The overall infectiousness is obtained according to the maximum infectious risk base and the sum of the actual infectious risks.

[0029] Optionally, the test result includes the contagion width;

[0030] The test results are obtained according to the evaluation data corresponding to all test users, including:

[0031] According to the evaluation data corresponding to all test users, the maximum infection value and the actual infection value of all test users are obtained;

[0032] The infection width is obtained according to the maximum infection value and the actual infection value.

[0033] According to a second aspect of an embodiment of the present disclosure, a test data processing device is provided, the device comprising:

[0034] An acquisition module is configured to acquire test data of each test user, where the test data of each test user is test data corresponding to the test device worn by each test user;

[0035] An acquisition module is configured to determine the evaluation data corresponding to each test user according to the test data of each test user, wherein the evaluation data corresponding to each test user includes the risk baseline score corresponding to the test user and the infection risk score corresponding to each test user associated with the test user;

[0036] The sending module is configured to obtain the test result according to the evaluation data corresponding to all the test users.

[0037] According to a third aspect of an embodiment of the present disclosure, a test system is provided, including:

[0038] at least one test cluster, each test cluster including a plurality of test devices;

[0039] A switch group, wherein the switch group is connected to each test cluster respectively;

[0040] A positioning server, the positioning server is connected to the switch group;

[0041] A test application server, the test application server is connected to the switch group, and the test application server is used to execute the steps of the test data processing method provided in the first aspect of the present disclosure.

[0042] Optionally, each test cluster includes a terminal cluster, a positioning network system, and a communication network system;

[0043] Each terminal cluster includes a plurality of the test devices, and each test device is respectively connected to the positioning network system and the communication network system;

[0044] The positioning network system and the communication network system are respectively connected to the switch group.

[0045] Optionally, the switch group includes a convergence switch and at least one basic switch;

[0046] Each of the basic switches is connected to a test cluster;

[0047] Each basic switch is connected to the aggregation switch respectively.

[0048] Optionally, the testing device comprises:

[0049] A test terminal carrier, wherein the test terminal carrier is used for being worn by a test user;

[0050] A test terminal body, wherein the test terminal body is arranged on the test terminal carrier;

[0051] A communication device, the communication device is arranged on the test terminal carrier, and the communication device is connected to the test terminal body;

[0052] A camera is arranged on the test terminal carrier and connected to the test terminal body.

[0053] Optionally, the test terminal body includes a positioning module, a communication module, a battery assembly, a storage module, a gyroscope sensor and a controller;

[0054] The positioning module, the communication module, the battery assembly, the storage module, the gyroscope sensor and the camera are respectively connected to the controller;

[0055] The positioning module and the communication module are connected to the communication device respectively.

[0056] Optionally, the communication device includes a positioning antenna and a communication antenna, and the positioning antenna and the communication antenna are respectively connected to the test terminal body.

[0057] Optionally, the test terminal carrier is a hat, and the hat includes a hat body and a brim;

[0058] A roof-falling space is arranged at the top of the cap body, and the test terminal body and the communication device are both arranged in the roof-falling space;

[0059] The camera is arranged at the bottom of the hat brim.

[0060] According to a fourth aspect of an embodiment of the present disclosure, there is provided an electronic device, including:

[0061] a memory having a computer program stored thereon;

[0062] The processor is used to execute the computer program in the memory to implement the steps of the test data processing method provided in the first aspect of the present disclosure.

[0063] According to a fifth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored. When the program instructions are executed by a processor, the steps of the test data processing method provided in the first aspect of the present disclosure are implemented.

[0064] Through the above technical solution, the test data of each test user is obtained. The test data of each test user is the test data corresponding to the test device worn by each test user. According to the test data of each test user, the evaluation data corresponding to each test user is determined. The evaluation data corresponding to each test user includes the risk baseline score corresponding to the test user and the infection risk score corresponding to each test user associated with the test user. According to the evaluation data corresponding to all test users, the test results are obtained. Through the above method, the test data of each test user is obtained, and the test data of all users are analyzed to obtain the overall test results for the epidemic prevention system, so as to clarify the deficiencies of the existing epidemic prevention system, so as to optimize the existing epidemic prevention system according to the test results.

[0065] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings:

[0067] Figure 1The figure is a flow chart of a test data processing method according to an exemplary embodiment.

[0068] Figure 2 The present invention is a flowchart of a method for determining evaluation data according to an exemplary embodiment.

[0069] Figure 3 The figure is a flow chart showing a method for determining a test group in which infectious behavior occurs according to an exemplary embodiment.

[0070] Figure 4 The figure is a flow chart showing a method for determining a total infection risk score according to an exemplary embodiment.

[0071] Figure 5 It is a schematic diagram of the structure of a testing system according to an exemplary embodiment.

[0072] Figure 6 It is a schematic diagram of the structure of another testing system according to an exemplary embodiment.

[0073] Figure 7 It is a schematic structural diagram of a testing device according to an exemplary embodiment.

[0074] Figure 8 The figure is a schematic diagram showing the structure of a test terminal body and a communication device according to an exemplary embodiment.

[0075] Fig. 9 The figure is a block diagram of a test data processing device according to an exemplary embodiment.

[0076] Fig.10 It is a block diagram of an electronic device according to an exemplary embodiment.

[0077] Description of Reference Numerals

[0078] 51. Test application server; 52. Positioning server; 53. Switch group; 531. Aggregation switch; 532. Basic switch; 54. Test cluster; 541. Terminal cluster; 542. Positioning network system; 543. Communication network system; 71. Test terminal carrier; 711. Cap body; 712. Cap brim; 72. Test terminal body; 721. Positioning module; 722. Communication module; 723. Battery assembly; 724. Storage module; 725. Gyroscope sensor; 726. Controller; 73. Communication device; 731. Positioning antenna; 732. Communication antenna; 74. Camera. DETAILED DESCRIPTION

[0079] The specific implementation of the present disclosure is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.

[0080] In the related technologies, the testing and verification technologies are all for testing and verification of their individual functions. Verify whether there are prompts for broadcast information. Verify whether the system issues an alarm when the distance between passengers is too small or the masks are not worn correctly. There is no overall and direct evaluation of the epidemic prevention effect of the epidemic prevention system, and it is impossible to optimize the existing epidemic prevention system based on these prompts in the testing and verification method.

[0081] In response to the above problems, the embodiments of the present disclosure provide a test data processing method, device, test system, electronic device and medium, which obtain the test data of each test user and analyze the test data of all users to obtain the overall test results, so as to optimize the existing epidemic prevention system according to the test results.

[0082] Figure 1 is a flow chart of a test data processing method according to an exemplary embodiment. Figure 1 As shown, the method can be applied to test the application server, and the method includes the following steps:

[0083] In step S101, the test data of each test user is obtained, where the test data of each test user is the test data corresponding to the test device worn by each test user.

[0084] In this embodiment, there may be multiple test users, each of whom wears a test device, and the test device is used to collect raw data of the test user. The raw data may include first raw data and second raw data. Each test device directly sends the collected first raw data to the test application server, and sends the second raw data to the positioning server, which is processed by the positioning server to obtain positioning data. The test application server can obtain test data based on the first raw data and the positioning data.

[0085] In step S102, based on the test data of each test user, the evaluation data corresponding to each test user is determined, and the evaluation data corresponding to each test user includes the risk baseline score corresponding to the test user and the infection risk score corresponding to each test user associated with the test user.

[0086] After obtaining the test data of each test user, it is possible to determine whether contagion occurs between any two test users, and process the test data of each test user according to the judgment result to obtain the evaluation data corresponding to each test user. The evaluation data corresponding to each test user includes the risk baseline score corresponding to the test user and the infection risk score corresponding to each test user associated with the test user. For example, the risk baseline score corresponding to each test user may be 100, and the test users associated with the test user include the test users who have direct infection with the test user and the test users who have indirect infection with the test user.

[0087] In step S103, the test results are obtained according to the evaluation data corresponding to all the test users.

[0088] After determining the evaluation data corresponding to each test user, the epidemic prevention result of the epidemic prevention system can be calculated to obtain the test result. The test result may include at least one of the following: infection width, overall infection degree and infection density.

[0089] Through the above method, the test data of each test user is obtained, and the test data of all users is analyzed to obtain the overall test results for the epidemic prevention system, so as to clarify the deficiencies of the existing epidemic prevention system and optimize the existing epidemic prevention system according to the test results.

[0090] Figure 2 is a flow chart showing a method for determining evaluation data according to an exemplary embodiment. Figure 2 As shown, in a feasible implementation manner, the test data may include the duration and facial monitoring results of any two test users detected in each relative distance range, and the evaluation data corresponding to each test user is determined according to the test data of each test user, including the following steps:

[0091] In step S201, according to the duration of any two test users in each relative distance range, a test group where infectious behavior occurs is determined, and each test group includes two test users.

[0092] In this embodiment, multiple relative distance ranges may be set, for example, greater than or equal to 100 cm, 100 cm-70 cm, 70 cm-40 cm, and less than 40 cm. The test application server may monitor the distance between any two test users and the duration of any two test users in each relative distance range in real time based on the first original data and the positioning data. Any two test users who have infectious behavior may be determined based on the duration of any two test users in each relative distance range, and any two test users who have infectious behavior may be determined as a test group, where any two test users who have infectious behavior are any two test users who directly have infectious behavior.

[0093] In step S202, the total infection risk score between the two test users included in each test group is determined according to the duration and facial monitoring results of any two test users in each relative distance range.

[0094] Among them, the facial monitoring results can be obtained through the camera on the test device and the test terminal body. Different relative distance ranges correspond to different infection risk coefficients, and different facial monitoring results also correspond to different infection risk coefficients. The total infection risk score between the two test users included in each test group can be determined based on the duration of any two test users in each relative distance range and the different infection coefficients.

[0095] In step S203, the evaluation data corresponding to each test user is determined according to the total infection risk score of all test groups.

[0096] Based on the total infection risk score of each test group, the infection data of the two test users included in the test group can be updated respectively. After the infection data of the test users included in all the test groups are updated, the evaluation data corresponding to each test user can be obtained.

[0097] In this embodiment, according to the characteristics of epidemic transmission, according to the time of close contact between two test users, and facial monitoring results, such as whether they wear masks, etc., a more accurate total infection risk score is calculated to update the infection data of each test user, and taking into account the existence of direct infection and indirect infection, the evaluation data corresponding to each test user is determined according to the total infection risk score of all test groups, so that the evaluation data of each test user can include the data of all possible directly infected test users and the data of indirectly infected test users, thereby making the test results more accurate.

[0098] Figure 3 is a flow chart showing a method for determining a test group in which infectious behavior occurs according to an exemplary embodiment. Figure 3As shown, in a feasible implementation manner, determining a test group where infectious behavior occurs according to the duration of any two test users in each relative distance range includes the following steps:

[0099] In step S301, for any two test users, the duration during which the relative distance between the any two test users is less than the infectious distance is determined according to the duration during which the any two test users are in each relative distance range.

[0100] In this embodiment, the duration that the relative distance between the two test users is less than the infectious distance is determined based on the duration that the two test users are in each relative distance range. For example, if the infectious distance is 100 cm, the duration that the two test users are between 100 cm and 70 cm is 5 seconds, and the duration that the two test users are between 70 cm and 40 cm is 4 seconds. At this time, the duration that the relative distance between the two test users is less than the infectious distance is the sum of multiple durations less than 100 cm, that is, 9 seconds.

[0101] In step S302, when the relative distance between the arbitrary two test users is less than the contagion distance for a duration greater than the contagion time, the arbitrary two test users are determined as a test group in which contagious behavior occurs.

[0102] In this embodiment, the relationship between the duration of the relative distance between any two test users being less than the infectious distance and the infectious time is determined. When the duration of the relative distance between any two test users being less than the infectious distance is greater than the infectious time, the two test users are determined as a test group that has infectious behavior. For example, if the infectious time is 8 seconds and the duration of the relative distance between any two test users being less than the infectious distance is 9 seconds, the two test users are determined as a test group that has infectious behavior.

[0103] Figure 4 is a flow chart of a method for determining a total infection risk score according to an exemplary embodiment. Figure 4 As shown, in a feasible implementation, the facial monitoring result includes the orientation of the test device and the facial image of the test user, and the total infection risk score between the two test users included in each test group is determined by the duration and facial monitoring results of any two test users in each relative distance range, including the following steps:

[0104] In step S401, the mask wearing status and relative facial angle of any two test users in each relative distance range are determined according to the orientation of the test device and the facial images of the test users.

[0105] Among them, the facial monitoring results can be obtained through the camera on the test device and the test terminal body. For example, the orientation of the test device can be determined by the gyroscope sensor contained in the test terminal body on the test terminal. Then, according to the facial image of the test user, the angle between the front of the test user and the test device is determined. According to the angle between the front of the test user and the test device, and the orientation of the test device, the facial orientation of the test user can be determined. According to the facial orientation of any two test users, the relative facial angle of the two test users can be determined. The mask wearing status of the test user can be directly determined based on the facial image of the test user. By obtaining the test device orientation and the facial image of any two test users in each relative distance range, the mask wearing status and the relative facial angle of any two test users in each relative distance range can be obtained.

[0106] In step S402, the duration, mask wearing status and relative facial angle of any two test users within the infectious distance in each relative distance range are obtained respectively to obtain multiple groups of test data corresponding to any two test users.

[0107] In this embodiment, the data of any two test users in different relative distance ranges are processed separately. At this time, the duration, mask wearing status and relative facial angle of any two test users in each relative distance range within the infectious distance can be obtained respectively, and multiple groups of test data corresponding to any two test users are obtained. That is, each group of test data includes the duration, mask wearing status and relative facial angle of any two test users in the infectious distance in the same relative distance range.

[0108] In step S403, the infection risk sub-score corresponding to each group of test data is calculated.

[0109] In this embodiment, for each set of test data, an infection risk sub-score can be calculated. For example, the product of the sum of the infection risk coefficients and the duration can be determined as the infection risk sub-score. The sum of the infection risk coefficients is the sum of the infection risk coefficients corresponding to the relative distance range, the infection risk coefficients corresponding to the mask wearing state, and the infection risk coefficients corresponding to the relative angle of the face.

[0110] For example, for the relative distance range, the infection risk coefficient corresponding to 100cm-70cm may be 1, the infection risk coefficient corresponding to 70-40cm may be 4, and the infection risk coefficient corresponding to less than 40cm may be 8; for the mask wearing status, the infection risk coefficient corresponding to standard wearing of the mask may be 0, the infection risk coefficient corresponding to one party not wearing the mask in a standard manner may be 5, and the infection risk coefficient corresponding to both parties not wearing the mask in a standard manner may be 10; for the relative facial angle, the infection risk coefficient corresponding to greater than 90 degrees may be 0, the infection risk coefficient corresponding to 40 degrees-90 degrees may be 4, and the infection risk coefficient corresponding to 0 degrees-40 degrees may be 8. If a set of test data has a duration of 3 seconds in the relative distance range of 70cm-40cm, the mask wearing status is one party not wearing the mask in a standard manner, and the relative facial angle is 40 degrees-90 degrees, then the infection risk sub-score corresponding to the set of test data is calculated to be: 3×(4+5+4)=39.

[0111] In step S404, the infection risk sub-scores corresponding to multiple groups of test data corresponding to any two test users are summed to obtain a total infection risk score between the two test users included in each test group.

[0112] After obtaining the infection risk sub-score corresponding to each group of test data, the multiple infection risk sub-scores corresponding to any two test users are summed to obtain the total infection risk score between the two test users in each test group. A total infection risk score threshold can be set, for example, the total infection risk score threshold is 100, that is, the maximum total infection risk score can be 100, and if it exceeds 100, it is calculated as 100.

[0113] In this embodiment, each relative distance range has different infection risks, and different mask wearing states and relative facial angles all have different infection risks. By obtaining multiple groups of test data based on the duration, mask wearing state and relative facial angle of any two test users within the infection distance in each relative distance range, and calculating the infection risk sub-score of each group of test data respectively, and then calculating the total infection risk score, the obtained total infection risk score can be made more accurate.

[0114] In a feasible embodiment, the evaluation data corresponding to each test user is determined according to the total infection risk score of all test groups, including:

[0115] Based on the order in which infectious behaviors occur in the test groups and according to the total infection risk score of each test group, the infection data of the test users included in each test group are updated in sequence to obtain the evaluation data corresponding to each test user.

[0116] In this embodiment, based on the order in which infectious behaviors occur in each test group, when it is determined that infectious behaviors occur between two test users, the infection data of the test users included in the test group can be updated according to the total infection risk score of the test group. After the infection data of the test users of all test groups are updated, the evaluation data corresponding to each test user can be obtained.

[0117] Among them, the initial infection data of each test user includes the risk baseline score corresponding to the test user, and the size of the risk baseline score can be the threshold of the total infection risk score. If the initial two test users have infectious behavior and their total infection risk score is 60, then the infection data of the two updated test users can respectively include their own risk baseline scores and the infection risk score corresponding to the other test user in the test group, wherein the infection risk score corresponding to the other test user is the total infection risk score corresponding to the test group.

[0118] For example, assume that an infectious behavior occurs between test user A and test user B, and the total infection risk score is 60.

[0119] The infection data before the update of A is shown in the following table:

[0120] ID A101 (own) 110(C) 119(D) value 100 100 50

[0121] The infection data of B before the update is shown in the following table:

[0122] ID B102 (own) 120(C) 129(E) value 100 40 70

[0123] After the infection behavior, the infection data of A and B are updated. At this time,

[0124] The updated infection data of Person A is shown in the following table:

[0125]

[0126] The updated infection data of B is shown in the following table:

[0127]

[0128] Among them, all the infection data corresponding to B need to be updated to A based on the total infection risk score, and all the data in A need to be updated to B based on the total infection risk score. For example, each test user corresponds to an ID (Identity document). If the total infection risk score between A and B is 60, then add B's ID and its corresponding total infection risk score 60 to A's infection data, add A's ID and its corresponding total infection risk score 60 to B's infection data, and update the data of other test users contained in A's infection data to B. Among them, if there is also the same test user in B, such as C, at this time, first determine the size of C's value and the total infection risk score. If it is greater than the total infection risk score, only the value of the total infection score is passed; if it is less than the total infection risk score, the actual value itself is passed. Then, the largest value among the values ​​corresponding to the same test users in A or B is determined as the final value. For example, if the value of C in A is 100, which is greater than or equal to the total infection risk score of 60, then only 60 is passed to B. At this time, 60 is greater than 40, so the value of C in B's infection data is determined to be 60. If the value of C in B is 40, which is less than the total infection risk score of 60, then 40 is passed to A. At this time, 100 in A is greater than 40, so the value of C in A's infection data is determined to be 100.

[0129] If there is a test user in B that does not exist in A, such as E, then E will be updated to the infection data of A. If the value of E is greater than or equal to the total infection risk score, only the value of the total infection risk score will be passed. If the value of E is less than the total infection risk score, the actual value will be passed. For example, if the value of E in B is 70, which is greater than 60, the value passed to A is 60.

[0130] In a feasible implementation, the test result may include the overall infectiousness, and the test result is obtained according to the evaluation data corresponding to all test users, including:

[0131] According to the evaluation data corresponding to all test users, the maximum infection risk base and the sum of actual infection risks of all test users are obtained;

[0132] The overall degree of infection is obtained based on the maximum infection risk base and the sum of actual infection risks.

[0133] In this embodiment, the test results may include the overall infectiousness, and the effectiveness of the current epidemic prevention system can be determined by the overall infectiousness.

[0134] For example, there are n test users participating in this test, and their ID numbers are 1 to n. Among them, the maximum contagious risk base is that all test users have transferred their risk base points to all other test users.

[0135] The maximum risk base of a person's infection is: 100+(n-1)100=100n.

[0136] Then the maximum infection base of n people is:

[0137] Maximum infection risk base = n*(100+(n-1)100) = n*n*100

[0138] That is, each test terminal has the total risk score of all test terminals.

[0139] The infection risk value of each person from the 1st to the nth person is recorded as X1 to Xn, then the infection risk value of all people is X1+X2...+Xn-1+Xn, and the value range of X is from 100 at the minimum to 100n at the maximum. Then:

[0140] The total actual infection risk = X1+X2...+Xn-1+Xn

[0141] Overall infection rate = [(X1+X2...+Xn-1+Xn) / n*n*100]*100%

[0142] In a feasible implementation, the test result may include the infection width, and the test result is obtained according to the evaluation data corresponding to all the test users, including:

[0143] According to the evaluation data corresponding to all test users, the maximum infection value and the actual infection value of all test users are obtained;

[0144] The infection width is obtained according to the maximum infection value and the actual infection value.

[0145] In this embodiment, the test result may include the infection width, and the effectiveness of the current epidemic prevention system can be determined by the infection width.

[0146] In this embodiment, the infection score value is not considered, only whether the infection occurs is considered, so only the number of IDs in the test data corresponding to each test user is counted.

[0147] Assuming that there are n test users participating in this test, there are n IDs.

[0148] No test user is infected. Each test user has only one ID. The sum of the IDs of n test users is n, which is the minimum infection width n.

[0149] All test users infect each other, and each test user has the IDs of all other test users, that is, there are n IDs. Then the sum of the IDs of n people is n*n, that is, the maximum infection width is n*n;

[0150] After the test, the ID number of each person from the 1st to the nth person is recorded as Y1....Yn

[0151] Then the sum of all people's IDs is Y1+Y2...+Yn-1+Yn, and the value range of Y is from 1 at the minimum to n at the maximum, then:

[0152] Infection width = [(Y1+Y2...+Yn-1+Yn) / n*n]*100%

[0153] Figure 5 is a schematic structural diagram of a test system according to an exemplary embodiment. Figure 6 is a schematic diagram of the structure of another test system according to an exemplary embodiment. Figure 5 and Figure 6 As shown, the embodiment of the present disclosure also provides a testing system, including:

[0154] at least one test cluster 54, each test cluster 54 comprising a plurality of test devices;

[0155] A switch group 53, the switch group 53 is connected to each test cluster 54 respectively;

[0156] A positioning server 52, the positioning server 52 is connected to a switch group 53;

[0157] The test application server 51 is connected to the switch group 53 and is used to execute the test data processing method.

[0158] In this embodiment, each test cluster 54 may include a terminal cluster 541, a positioning network system 542 and a communication network system 543. Each terminal cluster 541 may include multiple test devices, each test device is respectively connected to the positioning network system 542 and the communication network system 543, and the positioning network system 542 and the communication network system 543 are respectively connected to the switch group 53.

[0159] The switch group 53 may include an aggregation switch 531 and at least one basic switch 532, each basic switch 532 is connected to a test cluster 54, and each basic switch 532 is respectively connected to the aggregation switch 531. The positioning network system 542 and the communication network system 543 are respectively connected to the basic switches 532 of the switch group 53. The communication network system 543 may include at least one access AP (Access Point), and the positioning network system 542 may include multiple base stations.

[0160] Access APs and base stations are reasonably installed and arranged according to the scene area division. This can include station platform areas, vehicle areas, station hall areas and other public service areas. Among them, the base station can locate the test terminal through UWB (Ultra Wide Band) positioning.

[0161] For example, multiple test clusters 54 can be divided according to the geographical scope, each test cluster 54 includes multiple test users, each test user wears a test device, the test device is used to collect the original data of the test user, including the direction of the test device, the facial image of the test user and the positioning information of the test user, the test device sends the positioning information of the test user to the positioning network system 542, the positioning network system 542 processes the positioning information through multiple base stations to obtain multiple positioning data, and transmits the multiple positioning data to the positioning server 52 through the basic switch 532 and the aggregation switch 531, the positioning server 52 processes the multiple positioning data to obtain the positioning result of the test device, and then obtains the positioning result of the corresponding test user, thereby obtaining the distance information of any two test users among all the test users and the time they exist in the distance interval. The positioning server 52 can send the distance information of any two test users and the time they exist in the distance interval to the test application server 51, so that the test application server 51 obtains the duration of any two test users in each relative distance range based on the distance information of any two test users and the time they exist in the distance interval.

[0162] The test device can transmit the orientation of the test device and the facial image of the test user to the positioning server 52 through the communication network system 543, the basic switch 532 and the aggregation switch 531. The positioning server 52 can determine the evaluation data of each test user based on the test data received from each test user (including the orientation of the test device of each test user, the facial image of the test user and the duration of any two test users in each relative distance range), and obtain the test results based on the corresponding evaluation data of all test users.

[0163] Figure 7 is a schematic structural diagram of a testing device according to an exemplary embodiment. Figure 8 is a schematic diagram showing the structure of a test terminal body 72 and a communication device 73 according to an exemplary embodiment. Figure 7 and Figure 8 As shown, in a feasible implementation, the testing device may include:

[0164] A test terminal carrier 71, the test terminal carrier 71 is used for testing the user wearing it;

[0165] A test terminal body 72, which is disposed on a test terminal carrier 71;

[0166] A communication device 73, which is disposed on the test terminal carrier 71 and is connected to the test terminal body 72;

[0167] The camera 74 is disposed on the test terminal carrier 71 , and the camera 74 is connected to the test terminal body 72 .

[0168] In this embodiment, the test terminal carrier 71 is used for the test user to wear, and is used to carry the test terminal body 72, the communication device 73 and the camera 74. For example, the test terminal carrier 71 can be a hat, which includes a hat body 711 and a brim 712. A roof space is set at the top of the hat body 711, and the test terminal body 72 and the communication device 73 are both set in the roof space. The camera 74 is set at the bottom of the brim 712, and the camera 74 is connected to the test terminal body 72 through a signal line. The signal line can be distributed along the hat body 711 and the brim 712.

[0169] Among them, the test terminal body 72 may include a positioning module 721, a communication module 722, a battery assembly 723, a storage module 724, a gyroscope sensor 725 and a controller 726. The positioning module 721, the communication module 722, the battery assembly 723, the storage module 724, the gyroscope sensor 725 and the camera 74 are respectively connected to the controller 726, and the positioning module 721 and the communication module 722 are respectively connected to the communication device 73, wherein the communication device 73 may include a positioning antenna 731 and a communication antenna 732, and the positioning antenna 731 and the communication antenna 732 may be respectively connected to the positioning module 721 and the communication module 722 of the test terminal body 72.

[0170] Among them, the controller 726 runs the lower computer software for receiving the control of the upper computer software of the test application server 51, and is responsible for overall control of the test device. The storage module 724 is connected to the controller 726 for storing data of the test device. The battery assembly 723 is connected to the controller 726 for powering the test device. The communication module 722 is connected to the controller 726, responsible for wifi communication, and an external wifi communication antenna 732. The positioning module 721 is connected to the controller 726, responsible for positioning through the base station, and an external positioning antenna 731. The gyroscope sensor 725 is connected to the controller 726, responsible for determining the direction of the test device. The camera 74 is connected to the controller 726 for obtaining the facial image of the test user.

[0171] Fig. 9 is a block diagram of a test data processing device according to an exemplary embodiment, referring to Fig. 9The device includes an acquisition module 901, a determination module 902 and an obtaining module 903.

[0172] The acquisition module 901 is configured to acquire the test data of each test user, where the test data of each test user is the test data corresponding to the test device worn by each test user;

[0173] The determination module 902 is configured to determine the evaluation data corresponding to each test user according to the test data of each test user, wherein the evaluation data corresponding to each test user includes the risk baseline score corresponding to the test user and the infection risk score corresponding to each test user associated with the test user;

[0174] The obtaining module 903 is configured to obtain the test result according to the evaluation data corresponding to all the test users.

[0175] Optionally, the test data includes the duration and facial monitoring results of any two test users detected in each relative distance range;

[0176] The determining module 902 includes:

[0177] A first determination submodule is configured to determine a test group where infectious behavior occurs according to the duration of any two test users in each relative distance range, each test group including two test users;

[0178] The second determination submodule is configured to determine the total infection risk score between two test users included in each test group according to the duration and facial monitoring results of any two test users in each relative distance range;

[0179] The third determination submodule is configured to determine the evaluation data corresponding to each test user according to the total infection risk score of all test groups.

[0180] Optionally, the first determining submodule includes:

[0181] A first determining subunit is configured to determine, for any two test users, a duration during which the relative distance between the any two test users is less than the infectious distance according to the duration during which the any two test users are in each relative distance range;

[0182] The second determining subunit is configured to determine the arbitrary two test users as a test group having infectious behavior when the relative distance between the arbitrary two test users is less than the infectious distance for a duration greater than the infectious time.

[0183] Optionally, the facial monitoring result includes the orientation of the test device and the facial image of the test user;

[0184] The second determining module 902 includes:

[0185] A third determination subunit is configured to determine the mask wearing status and relative facial angle of any two test users in each relative distance range according to the orientation of the test device and the facial image of the test user;

[0186] The first obtaining subunit is configured to respectively obtain the duration, mask wearing status and relative facial angle of any two test users within the infectious distance in each relative distance range, and obtain multiple groups of test data corresponding to any two test users;

[0187] The second obtaining subunit is configured to calculate, based on each set of test data, the infection risk sub-score corresponding to the set of test data;

[0188] The third obtaining subunit is configured to sum up the infection risk sub-scores corresponding to multiple groups of test data corresponding to any two test users, to obtain a total infection risk score between the two test users included in each test group.

[0189] Optionally, the third determining module 902 includes:

[0190] The fourth obtaining subunit is configured to update the infection data of the test users included in each test group in sequence based on the order in which the infection behaviors of the test groups occur and according to the total infection risk score of each test group, to obtain the evaluation data corresponding to each test user.

[0191] Optionally, the test results include overall infectivity;

[0192] The obtaining module 903 includes:

[0193] A first obtaining submodule is configured to obtain the maximum infection risk base and the sum of actual infection risks of all test users according to the evaluation data corresponding to all test users;

[0194] The second obtaining submodule is configured to obtain the overall infection degree according to the maximum infection risk base and the sum of the actual infection risks.

[0195] Optionally, the test result includes the contagion width;

[0196] The obtaining module 903 includes:

[0197] The third obtaining submodule is configured to obtain the maximum infection value and the actual infection value of all the test users according to the evaluation data corresponding to all the test users;

[0198] The fourth obtaining submodule is configured to obtain the infection width according to the maximum infection value and the actual infection value.

[0199] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0200] Fig.10 FIG. 1 is a block diagram of an electronic device according to an exemplary embodiment. Fig.10 As shown, the electronic device 1000 may include: a processor 1001 and a memory 1002. The electronic device 1000 may also include one or more of a multimedia component 1003, an input / output interface 1004, and a communication component 1005.

[0201] The processor 1001 is used to control the overall operation of the electronic device 1000 to complete all or part of the steps in the above-mentioned test data processing method. The memory 1002 is used to store various types of data to support the operation of the electronic device 1000, and these data may include, for example, instructions for any application or method used to operate on the electronic device 1000, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 1002 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk. The multimedia component 1003 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 1002 or sent through the communication component 1005. The audio component also includes at least one speaker for outputting audio signals. The input / output interface 1004 provides an interface between the processor 1001 and other interface modules, and the other interface modules may be keyboards, mice, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 1005 is used for wired or wireless communication between the electronic device 1000 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more of them, is not limited here. Therefore, the corresponding communication component 1005 may include: Wi-Fi module, Bluetooth module, NFC module, etc.

[0202] In an exemplary embodiment, the electronic device 1000 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned test data processing method.

[0203] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned test data processing method are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 1002 including program instructions, and the above-mentioned program instructions can be executed by the processor 1001 of the electronic device 1000 to complete the above-mentioned test data processing method.

[0204] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program executable by a programmable device. The computer program has a code portion for executing the above test data processing method when executed by the programmable device.

[0205] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0206] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0207] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A test data processing method, characterized in that: Applied to testing an application server, the method comprises: Acquire test data of each test user, where the test data of each test user is test data corresponding to the test device worn by each test user, and the test data includes the duration and facial monitoring results of any two test users detected in each relative distance range, and the facial monitoring results include the orientation of the test device and the facial image of the test user; Determine the evaluation data corresponding to each test user according to the test data of each test user, wherein the evaluation data corresponding to each test user includes the risk baseline score corresponding to the test user and the infection risk score corresponding to each test user associated with the test user; Get the test results based on the evaluation data corresponding to all test users; The step of determining the evaluation data corresponding to each test user according to the test data of each test user includes: For any two test users, determine the duration during which the relative distance between the two test users is less than the infectious distance based on the duration during which the two test users are in each relative distance range; When the relative distance between the arbitrary two test users is less than the infectious distance and the duration is greater than the infectious time, the arbitrary two test users are determined as a test group in which infectious behavior occurs, and each test group includes two test users; Determine the facial orientation of the test user according to the orientation of the test device and the angle between the front face of the test user and the test device, and determine the mask wearing status and relative facial angle of any two test users in each relative distance range according to the facial orientations of any two test users, where the angle between the front face of the test user and the test device is determined based on the facial image of the test user; The duration, mask wearing status and relative facial angle of any two test users within the infectious distance are obtained respectively in each relative distance range, and multiple groups of test data corresponding to any two test users are obtained; For any set of test data, the product of the sum of the infection risk coefficients and the duration is determined as the infection risk sub-score corresponding to the set of test data, and the sum of the infection risk coefficients is the sum of the infection risk coefficients corresponding to the relative distance range in the set of test data, the infection risk coefficients corresponding to the mask wearing state, and the infection risk coefficients corresponding to the relative angle of the face; Sum up the infection risk sub-scores corresponding to multiple groups of test data corresponding to any two test users to obtain the total infection risk score between the two test users included in each test group; Based on the order in which the infectious behaviors of the test groups occur and according to the total infection risk score of each test group, the infection data of the test users included in each test group are updated in sequence to obtain the evaluation data corresponding to each test user.

2. The test data processing method according to claim 1, characterized in that: The test results include overall infectivity; The test results are obtained according to the evaluation data corresponding to all test users, including: According to the evaluation data corresponding to all test users, the maximum infection risk base and the sum of actual infection risks of all test users are obtained; The overall infectiousness is obtained according to the maximum infectious risk base and the sum of the actual infectious risks.

3. The test data processing method according to claim 1, characterized in that: The test results include contagion width; The test results are obtained according to the evaluation data corresponding to all test users, including: According to the evaluation data corresponding to all test users, the maximum infection value and the actual infection value of all test users are obtained; The infection width is obtained according to the maximum infection value and the actual infection value.

4. A test data processing device, characterized in that: The device comprises: An acquisition module is configured to acquire test data of each test user, wherein the test data of each test user is test data corresponding to a test device worn by each test user, wherein the test data includes a duration and a facial monitoring result of any two test users detected in each relative distance range, wherein the facial monitoring result includes a direction of the test device and a facial image of the test user; A determination module is configured to determine the evaluation data corresponding to each test user according to the test data of each test user, wherein the evaluation data corresponding to each test user includes the risk baseline score corresponding to the test user and the infection risk score corresponding to each test user associated with the test user; The obtaining module is configured to obtain the test results according to the evaluation data corresponding to all the test users; Wherein, the determination module includes: A first determining subunit is configured to determine, for any two test users, a duration during which the relative distance between the any two test users is less than the infectious distance according to the duration during which the any two test users are in each relative distance range; A second determining subunit is configured to determine the arbitrary two test users as a group of test groups in which infectious behavior occurs when the relative distance between the arbitrary two test users is less than the infectious distance and the duration is greater than the infectious time, each test group including two test users; A third determination subunit is configured to determine the facial orientation of the test user according to the orientation of the test device and the angle between the front face of the test user and the test device, and determine the mask wearing status and relative facial angle of any two test users in each relative distance range according to the facial orientations of any two test users, wherein the angle between the front face of the test user and the test device is determined according to the facial image of the test user; The first obtaining subunit is configured to respectively obtain the duration, mask wearing status and relative facial angle of any two test users within the infectious distance in each relative distance range, and obtain multiple groups of test data corresponding to any two test users; The second obtaining subunit is configured to determine, for any set of test data, the product of the sum of the infection risk coefficients and the duration as the infection risk sub-score corresponding to the set of test data, wherein the sum of the infection risk coefficients is the sum of the infection risk coefficients corresponding to the relative distance range in the set of test data, the infection risk coefficients corresponding to the mask wearing state, and the infection risk coefficients corresponding to the relative angle of the face; A third obtaining subunit is configured to sum the infection risk sub-scores corresponding to multiple groups of test data corresponding to any two test users to obtain a total infection risk score between the two test users included in each test group; The fourth obtaining subunit is configured to update the infection data of the test users included in each test group in sequence based on the order in which the infection behaviors of the test groups occur and according to the total infection risk score of each test group, to obtain the evaluation data corresponding to each test user.

5. A testing system, characterized in that: include: at least one test cluster, each test cluster including a plurality of test devices; A switch group, wherein the switch group is connected to each test cluster respectively; A positioning server, the positioning server is connected to the switch group; A test application server, the test application server is connected to the switch group, and the test application server is used to execute the steps of the method in any one of claims 1-3.

6. The test system according to claim 5, characterized in that: Each test cluster includes a terminal cluster, a positioning network system, and a communication network system; Each terminal cluster includes a plurality of the test devices, and each test device is respectively connected to the positioning network system and the communication network system; The positioning network system and the communication network system are respectively connected to the switch group.

7. The test system according to claim 6, characterized in that: The switch group includes an aggregation switch and at least one basic switch; Each of the basic switches is connected to a test cluster; Each basic switch is connected to the aggregation switch respectively.

8. The test system according to claim 5, characterized in that: The testing device comprises: A test terminal carrier, wherein the test terminal carrier is used for being worn by a test user; A test terminal body, wherein the test terminal body is arranged on the test terminal carrier; A communication device, the communication device is arranged on the test terminal carrier, and the communication device is connected to the test terminal body; A camera is arranged on the test terminal carrier and connected to the test terminal body.

9. The test system according to claim 8, characterized in that: The test terminal body includes a positioning module, a communication module, a battery assembly, a storage module, a gyroscope sensor and a controller; The positioning module, the communication module, the battery assembly, the storage module, the gyroscope sensor and the camera are respectively connected to the controller; The positioning module and the communication module are connected to the communication device respectively.

10. The test system according to claim 8, characterized in that: The communication device comprises a positioning antenna and a communication antenna, and the positioning antenna and the communication antenna are respectively connected to the test terminal body.

11. The test system according to claim 8, characterized in that: The test terminal carrier is a hat, and the hat includes a hat body and a brim; A roof-falling space is arranged at the top of the cap body, and the test terminal body and the communication device are both arranged in the roof-falling space; The camera is arranged at the bottom of the hat brim.

12. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the test data processing method described in any one of claims 1 to 3 are implemented.

13. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor is used to execute the computer program in the memory to implement the steps of the test data processing method according to any one of claims 1 to 3.

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