Big Data-Based Infectious Source Location Method, System, and Storage Medium

Abstract

A method, system and storage medium for locating the source of infection based on big data. The method includes: calculating and updating the personnel safety levels of each target person at each moment according to the personnel safety level of the target person at the previous moment of the first current moment, the personnel safety level determined based on detection information, the infection transmission probability, the regional risk level, and the probability of the target person being infected by the surrounding environment; the first current moment and the previous moment of the first current moment are separated by a first time period, and the initial personnel safety levels of each target person are preset (S101); calculating the regional risk level of the target location at the second current moment according to the regional risk level, disinfection coefficient, personnel safety level, infection transmission probability from infected person to the environment, and source of infection dissipation coefficient at the previous moment of the second current moment, and calculating and updating the regional risk levels of each target location at each moment; the second current moment and the previous moment of the second current moment are separated by a second time period, and the initial regional risk levels of each target location are preset (S102); when an intelligent mobile terminal with a regional risk level higher than the set threshold enters the set Bluetooth interconnection range, an alarm prompt is given, and / or when an intelligent mobile terminal with a personnel safety level lower than the set personnel safety level threshold enters the set Bluetooth interconnection range, an alarm prompt is given (S103). The above method realizes the accurate location of the source of infection.

Description

Technical Field

[0001] The present invention relates to the technical field of big data positioning, and in particular to a method, a system and a storage medium for positioning the source of infection based on big data. Background Art

[0002] With the progress of technology, the means for people to obtain information have gradually increased. And obtaining information is relatively important for the prevention and control of the epidemic. In existing operations, the epidemic prevention and control measures mainly restrict interpersonal communication, which can, to a certain extent, inhibit the spread of the epidemic, but will also have a negative impact on normal production and life. Moreover, due to the limited information obtained, the above prevention and control measures cannot be specific to each person, each location and each moment.

[0003] In the existing epidemic prevention and control measures, the epidemic prevention and control software installed on the intelligent mobile terminal can be used to view the epidemic map, that is, to see the communities where the epidemic occurs. However, the activity tracks of the infectious spread population cannot be traced, and it does not have a real-time early warning function. In addition, it is also possible to send text messages to the operator, or obtain the health code through WeChat and other means, so as to obtain which provinces and cities the intelligent mobile terminal has been to in a recent period of time. However, the data is inaccurate and cannot be specific to the contact situation with the source of infection. Summary of the Invention

[0004] In view of this, a method, a system and a storage medium for positioning the source of infection based on big data are provided to solve the situation in the prior art where the source of infection cannot be accurately positioned, resulting in inadequate epidemic prevention and control measures.

[0005] The present invention adopts the following technical solutions:

[0006] In the first aspect, an embodiment of the present application provides a method for positioning the source of infection based on big data, and the method includes:

[0007] According to the personnel safety level of the target person at the previous moment of the first current moment, the personnel safety level determined based on the detection information, the infection transmission probability at the previous moment of the first current moment, the regional risk level at the previous moment of the first current moment, and the probability of the target person being infected by the surrounding environment, calculate and update the personnel safety level of each target person at each moment; wherein, there is a first time period between the first current moment and the previous moment of the first current moment, and the initial personnel safety level of each target person is preset.

[0008] Calculate the regional risk level of the target location at the second current moment based on the regional risk level at the previous moment of the second current moment, the disinfection coefficient at the previous moment of the second current moment, the personnel safety level at the previous moment of the second current moment, the transmission probability of infected persons to the environment, and the source dissipation coefficient, so as to calculate and update the regional risk levels of each target location at each moment; wherein, there is a second time period between the second current moment and the previous moment of the second current moment, and the initial regional risk levels of each target location are preset.

[0009] Give an alarm prompt for intelligent mobile terminals entering areas where the regional risk level is greater than the set regional risk level threshold, and / or give an alarm prompt when an intelligent mobile terminal with a personnel safety level lower than the set personnel safety level threshold enters the set Bluetooth interconnection range.

[0010] In a second aspect, an embodiment of the present application provides a source location system, which includes a server and at least one intelligent mobile terminal, wherein:

[0011] The server is used to obtain and update the map library, wherein the map library stores the regional risk levels of each location at each moment.

[0012] The server is used to obtain and update the personnel database, wherein the personnel database stores the personnel safety levels of each person at each moment.

[0013] The intelligent mobile terminal is used to obtain personnel basic information and personnel safety levels, and update the personnel safety levels.

[0014] The intelligent mobile terminal is used to display the map interface in real time, wherein the regional safety levels of each location are marked with set colors in the map interface.

[0015] The intelligent mobile terminal is used to query the historical running trajectories and personnel contact history information of personnel.

[0016] The intelligent mobile terminal is used to display the personnel safety levels obtained within the set distance of each intelligent mobile terminal.

[0017] In a third aspect, an embodiment of the present application provides a storage medium, which stores a computer program. When the computer program is executed by a processor, it implements each step in the method for locating the source of infection based on big data as described in the first aspect.

[0018] The present invention adopts the above technical solutions and does not strongly rely on infectious disease monitoring. When there is no infectious disease monitoring, the method can still calculate and update the regional risk levels at each location and each moment, and the personal safety levels of each person at each moment based on the big data of the movement of people, and provide an alarm function when entering a high-risk level area and when a person with a high-risk level enters the Bluetooth interconnection range. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flowchart of a method for locating the source of infection based on big data provided by an embodiment of the present invention;

[0020] Figure 2 is a schematic structural diagram of a system for locating the source of infection based on big data provided by an embodiment of the present invention;

[0021] Figure 3 is a schematic structural diagram of a system for locating the source of infection based on big data applicable in an embodiment of the present invention;

[0022] Figure 4 is a schematic diagram of a Bluetooth positioning algorithm applicable in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be described in detail below. Apparently, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other implementation manners obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope protected by the present invention.

[0024] First, the applicable scenarios of the embodiments of the present application will be described. The method for locating the source of infection can be applied to the control of infectious disease epidemics, and an epidemiological investigation report can also be intelligently generated using this method to guide epidemic prevention and control.

[0025] Embodiment

[0026] Figure 1 is a flowchart of a method for locating the source of infection based on big data provided by an embodiment of the present invention. This method can be executed by the system for locating the source of infection based on big data provided by an embodiment of the present invention. Referring to Figure 1 , the method can specifically include the following steps:

[0027] S101. Calculate and update the personnel safety level of each target person at each moment based on the personnel safety level of the target person at the previous moment of the first current moment, the personnel safety level determined based on the detection information, the infection transmission probability at the previous moment of the first current moment, the regional risk level at the previous moment of the first current moment, and the infection probability of the target person by the surrounding environment; where the first current moment and the previous moment of the first current moment are separated by a first time period, and the initial personnel safety level of each target person is preset.

[0028] Specifically, the personnel safety level needs to be updated in real time, and the reasons for the update include detection situations, contact personnel situations, and characteristics of the contact area, etc. Optionally, the first current moment is denoted as t, the first time period is denoted as t0, and the previous moment of the first current moment is denoted as t - t0. The initial personnel safety level of each target person can be set according to the initial personnel information of the target person, where the initial personnel information such as the initial location and initial protection measures, etc.

[0029] In a specific example, the calculation and update method of the personnel safety level of each target person at each moment includes:

[0030]

[0031] Among them, P(t - t0) is the personnel safety level of the target person at the moment t - t0; D(t) is the personnel safety level determined based on the detection information after detection at the moment t; P i (t - t0) is the personnel safety level of each person within the set distance obtained by the intelligent mobile terminal of the target person through Bluetooth interconnection; i is the personnel number, and the total number of people other than the target person is n; α i (t - t0) is the infection transmission probability; S(φ, θ, t - t0) is the regional risk level of the location (φ, θ) where the target person is at the moment t; β is the infection probability of the target person by the surrounding environment.

[0032] Optionally, the infection transmission probability is determined according to the relative positions of the intelligent mobile terminals of the infected person and each intelligent mobile terminal, and the protection measures of the infected person.

[0033] Optionally, the infection probability of the target person by the surrounding environment is determined according to the protection measures of the target person and the residence time of the target person in the surrounding environment.

[0034] Exemplarily, the distance calculation method between two intelligent mobile terminals includes:

[0035]

[0036] Where, Dist is the distance between two intelligent mobile terminals; RSSI1 is the signal strength received by the Bluetooth port of the first intelligent mobile terminal from the Bluetooth port of the second intelligent mobile terminal; RSSI2 is the signal strength received by the Bluetooth port of the second intelligent mobile terminal from the first intelligent mobile terminal; A1 is the Bluetooth channel attenuation coefficient under the condition of a standard 1-meter spacing; A tt is the environmental attenuation factor; δ is the environmental correction parameter.

[0037] Specifically, converting Bluetooth RSSI (Received Signal Strength Indication) to distance is through a fitting regression function, similar to the variation law of RSSI. In a specific example, the above-mentioned distance Dist is the estimated distance between two intelligent mobile terminals. Usually, according to the surrounding environment, the value of A1 can be given as 59, A tt value is 2, and the value of δ is 0.2.

[0038] In a specific example, the method for obtaining the position information in the case of a human body or an animal as a source of infection carrier in the embodiments of the present application is as follows:

[0039] By GPS (Global Positioning System) positioning, the position of the intelligent mobile terminal can be obtained. By positioning the beacon node through GPS, and further through Bluetooth positioning, a more accurate relative position can be obtained.

[0040] In a specific example, Figure 4 shows a schematic diagram of a Bluetooth positioning algorithm; as Figure 4 shown, there are three non-collinear beacon nodes A, B, C with known coordinates and an unknown node D. Among them, the three nodes A, B, and C are all within the communication radius of Dist. The coordinates of the three beacon nodes are (x1, y1), (x2, y2), and (x3, y3) respectively. From Equation (2), the distances from the three beacon nodes to the unknown node can be obtained as d1, d2, and d3 respectively. Let the coordinates of the unknown node D be (x, y), then:

[0041]

[0042] Taking the square difference of the distances and subtracting the equations in Equation (3) pairwise, the equations of the three lines l1, l2, and l3 in Figure 5 can be obtained:

[0043]

[0044] After processing the above formula (4), the coordinates (x, y) of the unknown node can be obtained:

[0045]

[0046] Grouping three beacon nodes into a group, the possible position of an unknown node can be obtained. If every three beacon nodes that meet the conditions around the unknown node are grouped into a group, the possible positions of m unknown nodes can be obtained.

[0047] In order to obtain the position of the unknown node more accurately, the weighted coefficient method is used to determine the weights of the coordinates participating in the calculation. Let:

[0048]

[0049] Where:

[0050]

[0051] Taking the partial derivatives of x and y in Equation (6) respectively, we can get:

[0052]

[0053] Solving the above equations, we can get:

[0054]

[0055] Point Is the unbiased estimate of the unknown node X(x, y). The difference between each possible position point and point P is used to measure the weight of each possible position point. Let:

[0056]

[0057] Then, the weight coefficients of each possible position point are:

[0058]

[0059] Finally, the final position of the unknown node is:

[0060]

[0061] The above is the method for obtaining position information in the case of a human or animal as an infection source carrier in the present invention. The following is the method for obtaining an infection source at a location.

[0062] Optionally, the infection transmission probability is negatively correlated with the relative positions of the infected person's intelligent mobile terminal and each intelligent mobile terminal, and the infection transmission probability is related to the protective measures of the infected person.

[0063] S102. Calculate the regional risk level of the target location at the second current moment based on the regional risk level, disinfection coefficient, personnel safety level, transmission probability of infected persons to the environment, and source of infection dissipation coefficient at the previous moment of the second current moment, so as to calculate and update the regional risk levels of each target location at each moment; where the second current moment and the previous moment of the second current moment are separated by a second time period, and the initial regional risk levels of each target location are preset.

[0064] Specifically, the regional risk level is updated in real time. The reasons for this update include personnel contamination, disinfection measures, and the extinction of the virus over time. The second current moment is denoted as t1, the first time period is denoted as Δt, and the previous moment of the first current moment is t1 - Δt. The initial regional risk levels of each target location can be preset according to relevant data provided by the disease control department.

[0065] In a specific example, the calculation method of the regional risk levels of each target location at each moment includes:

[0066]

[0067] where S(φ, θ, t1 - Δt) is the regional safety level of the location (φ, θ) at the moment t1 - Δt; C(t1) is the disinfection coefficient that eliminates the virus before the current area at the moment t1 after taking disinfection measures at the moment t1 in a set proportion; P i (t1 - Δt) is the personnel safety level of person i at the moment t1 - Δt; γ i (t1 - Δt) is the transmission probability of infected persons to the environment at the moment t1 - Δt; is the source of infection dissipation coefficient; τ is the attenuation coefficient; t2 - t1 is the residence time of the source of infection. The attenuation coefficient τ is related to the environment and surrounding materials.

[0068] Optionally, the transmission probability of infected persons to the environment is related to the protection measures of infected persons and the personnel safety level of infected persons.

[0069] S103. Give an alarm prompt for intelligent mobile terminals entering a regional risk level greater than the set regional risk level threshold, and / or give an alarm prompt when an intelligent mobile terminal with a personnel safety level less than the set personnel safety level threshold enters the set Bluetooth interconnection range.

[0070] Among them, the set Bluetooth interconnection range can be 30 meters. Specifically, in the actual application process, the regional risk level sets the regional risk level threshold, and the region is a high-risk level area. An alarm prompt is given to the intelligent terminal entering the high-risk level area. In addition, a person with a personnel safety level lower than the set personnel safety level threshold is a person with a high-risk level. When a high-risk person enters the set Bluetooth interconnection range, an alarm prompt is given to each intelligent mobile terminal.

[0071] In the embodiment of the present application, the infectious disease positioning method based on the intelligent mobile terminal and the cloud platform does not strongly rely on infectious disease monitoring. When there is no infectious disease monitoring, this method can still calculate and update the regional risk level of each location at each moment and the personnel safety level of each person at each moment according to the big data of the personnel flow situation, and provide an alarm function when entering a high-risk level area and when a high-risk level person enters the Bluetooth interconnection range.

[0072] Figure 2 It is a schematic structural diagram of an infectious source positioning system provided by an embodiment of the present invention. This system is applicable to execute a big data-based infectious source positioning method provided by an embodiment of the present invention. As Figure 2 shown, this system may specifically include a server 21 and at least one intelligent mobile terminal 22.

[0073] Among them, the server 21 is used to obtain and update the map library, where the map library stores the regional risk level of each location at each moment; the server 21 is used to obtain and update the personnel database, where the personnel database stores the personnel safety level of each person at each moment; the intelligent mobile terminal 22 is used to obtain the basic information of the personnel and the personnel safety level, and update the personnel safety level; the intelligent mobile terminal 22 is used to display the map interface in real time, where the regional safety level of each location is marked with a set color in the map interface; the intelligent mobile terminal 22 is used to query the historical running trajectory of the personnel and the personnel contact history information; the intelligent mobile terminal 22 is used to display the personnel safety level obtained within the set distance of each intelligent mobile terminal.

[0074] Specifically, a person carries one or more intelligent mobile terminals. The intelligent mobile terminal can be a smart phone, a smart watch or a smart bracelet, etc. The intelligent mobile terminal installs an intelligent mobile terminal application software, which is used to call the Bluetooth function, the mobile data function and the combined positioning function of the intelligent terminal, interact information with the server application software through the mobile data function, and interact information with the intelligent mobile terminals carried by surrounding people by calling the Bluetooth function. The server runs the server application software, which is used to interact information with a large number of intelligent mobile terminals through the Internet.

[0075] Exemplarily, the server application software can run on a cloud platform and can refresh the map library and personnel database in real time. Each intelligent mobile terminal can obtain the basic information of personnel, update the personnel safety level in real time, display the map interface in real time, query the historical running track of personnel and the safety level at that moment, and query the personnel contact history information. The real-time map interface displays the real-time map and marks the safety levels of different locations with colors, and at the same time displays the safety levels of the surrounding personnel obtained by Bluetooth interconnection within about 30 meters of the intelligent mobile terminal.

[0076] In a specific example, Figure 3 shows a schematic structural diagram of an infectious source location system based on big data, where 1 represents the target person, 2 represents the intelligent mobile terminal, 3 represents the international Internet, 4 represents the cloud platform, 5 represents the data transmission of the mobile network, 7 represents the short-distance circle of Bluetooth transmission, 8 represents the critical transmission distance circle of Bluetooth transmission, 11 represents the personnel within the short-distance circle of Bluetooth transmission of the target person 1, 12 represents the personnel within the critical transmission distance circle of Bluetooth transmission of the target person, and 13 represents the personnel outside the critical transmission distance circle of Bluetooth transmission of the target person.

[0077] In the embodiment of the present application, the infectious disease location system based on the intelligent mobile terminal and the cloud platform does not strongly rely on infectious disease monitoring. When there is no infectious disease monitoring, the system can still calculate and update the regional risk levels at each location and each moment, and the personnel safety levels of each person at each moment according to the big data of the personnel flow situation, and provide an alarm function when entering a high-risk level area and when a person with a high-risk level enters the Bluetooth interconnection range. And give the infectious disease risk distribution map of each location; it can analyze the infectious disease infection risk of personnel according to the big data formed by the recent personnel contact data of personnel.

[0078] Exemplarily, the data information transmitted through Bluetooth communication between the intelligent mobile terminals carried by personnel includes personnel identity information, personnel safety level, and the received Bluetooth signal strength, etc. The intelligent mobile terminal application software carried by personnel communicates with the cloud platform server software through mobile data, and the communication uses the mobile Internet method to exchange data. The cloud platform server software transmits key information to the intelligent mobile terminal application software, including real-time map information, the location information of high-risk personnel within a given distance around the person, and high-risk alarm information, etc. The intelligent mobile terminal application software transmits key information to the cloud platform server software, including personnel identity information, personnel safety level, personnel real-time location information, the number of surrounding personnel obtained by Bluetooth of the person's intelligent mobile terminal, and the corresponding safety levels of the surrounding personnel.

[0079] Therefore, in the embodiments of the present application, the personnel safety level information has a real-time update function. The reasons for this update include detection situations, the situations of contacted personnel, and the characteristics of the contact areas, etc. The safety level of the area has a real-time update function. The reasons for this update include the contamination of personnel, disinfection measures, and the apoptosis of the virus over time. The cloud platform server software records the safety information of personnel and the information of the contacted personnel of the personnel, and can generate a report of close contacts of sensitive personnel. The intelligent mobile terminal application software can display the epidemic safety map in real time and display the safety levels of the surrounding personnel. Based on this system, the software operator of the cloud platform server can, after obtaining authorization, conduct a comprehensive assessment of the epidemic situation, accurately locate the epidemic information, and provide rich big data support for the prevention and control of the epidemic.

[0080] The source of infection location system based on big data provided by the embodiments of the present invention can execute the source of infection location method based on big data provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0081] The embodiments of the present invention further provide a storage medium. The storage medium stores a computer program. When the computer program is executed by a processor, it realizes each step in the source of infection location method based on big data in the embodiments of the present invention: calculating and updating the personnel safety levels of each target person at each moment according to the personnel safety level of the target person at the previous moment of the first current moment, the personnel safety level determined based on detection information, the infection transmission probability at the previous moment of the first current moment, the regional risk level at the previous moment of the first current moment, and the probability of the target person being infected by the surrounding environment; wherein, there is a first time period between the first current moment and the previous moment of the first current moment, and the initial personnel safety levels of each target person are preset; calculating the regional risk level of the target location at the second current moment according to the regional risk level at the previous moment of the second current moment, the disinfection coefficient at the previous moment of the second current moment, the personnel safety level at the previous moment of the second current moment, the transmission probability from the infected person to the environment, and the source dissipation coefficient, so as to calculate and update the regional risk levels of each target location at each moment; wherein, there is a second time period between the second current moment and the previous moment of the second current moment, and the initial regional risk levels of each target location are preset; giving an alarm prompt for the intelligent mobile terminal that enters an area where the regional risk level is greater than the set regional risk level threshold, and / or giving an alarm prompt when an intelligent mobile terminal with a personnel safety level less than the set personnel safety level threshold enters the set Bluetooth interconnection range.

[0082] It can be understood that the same or similar parts in the above embodiments can be referred to each other, and the content not detailed in some embodiments can be seen in the same or similar content in other embodiments.

[0083] It should be noted that in the description of the present invention, the terms "first", "second", etc. are only used for descriptive purposes and cannot be construed as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "a plurality of" refers to at least two.

[0084] Any process or method description in a flowchart or otherwise described herein can be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present invention includes additional implementations where functions may be executed in a substantially simultaneous manner or in the reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0085] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0086] Those of ordinary skill in the art of the present technology can understand that all or part of the steps carried by the method of the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0087] In addition, each functional unit in various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into a module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0088] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disk, etc.

[0089] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0090] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for locating the source of infection based on big data, characterized in that, Including: Calculating and updating the personnel safety levels of each target person at each moment according to the personnel safety level of the target person at the previous moment of the first current moment, the personnel safety level determined based on the detection information, the infection transmission probability at the previous moment of the first current moment, the regional risk level at the previous moment of the first current moment, and the probability of the target person being infected by the surrounding environment; wherein, there is a first time period between the first current moment and the previous moment of the first current moment, the initial personnel safety levels of each target person are preset, the infection transmission probability is determined according to the smart mobile terminal of the infected person and the relative positions of each smart mobile terminal, and the protective measures of the infected person; Calculating the regional risk level of the target location at the second current moment according to the regional risk level at the previous moment of the second current moment, the disinfection coefficient at the previous moment of the second current moment, the personnel safety level at the previous moment of the second current moment, the transmission probability from the infected person to the environment, and the source dissipation coefficient, and calculating and updating the regional risk levels of each target location at each moment; wherein, there is a second time period between the second current moment and the previous moment of the second current moment, the initial regional risk levels of each target location are preset; Giving an alarm prompt for the smart mobile terminal entering a region where the regional risk level is greater than the set regional risk level threshold, and / or giving an alarm prompt when a smart mobile terminal with a personnel safety level less than the set personnel safety level threshold enters the set Bluetooth interconnection range; The calculation and update method of the personnel safety levels of each target person at each moment is as follows: Among them, P(t - t0) is the personnel safety level of the target person at time t - t0; D(t) is the personnel safety level determined according to the detection information after detection at time t; P i (t - t0) is the personnel safety level of each person within the set distance obtained by the intelligent mobile terminal of the target person through Bluetooth interconnection; i is the personnel number, and the total number of people other than the target person is n; α i (t - t0) is the infection transmission probability; S(Ф, θ, t - t0) is the regional risk level of the location (Ф, θ) where the target person is at time t - t0; β is the infection probability of the target person in the environment where they are located; The calculation method of the regional risk levels of each target location at each moment is as follows: Among them, S(Ф,θ,t1-△t) is the regional risk level at the position (Ф,θ) at the moment t1-△t; C(t1) is the disinfection coefficient that eliminates the virus in the current area before the moment t1 at a set ratio after taking disinfection measures at the moment t1; P i (t1-△t) is the personal safety level of person i at the moment t1-△t; γ i (t1-△t) is the transmission probability from the infected person to the environment at the moment t1-△t; is the source dissipation coefficient; τ is the attenuation coefficient; t2-t1 is the residence time of the source of infection; The distance calculation method between two smart mobile terminals is as follows: Wherein, Dist is the distance between two smart mobile terminals; RSSI1 is the signal strength received by the Bluetooth port of the first smart mobile terminal from the Bluetooth port of the second smart mobile terminal; RSSI2 is the signal strength received by the Bluetooth port of the second smart mobile terminal from the first smart mobile terminal; A1 is the Bluetooth channel attenuation coefficient in the case of a standard 1-meter spacing; Att is the environmental attenuation factor; δ is the environmental correction parameter.

2. The method according to claim 1, wherein The probability of the target person being infected by the surrounding environment is determined according to the protective measures of the target person and the residence time of the target person in the surrounding environment.

3. The method according to claim 1, characterized in that, The transmission probability from the infected person to the environment is determined according to the protective measures of the infected person and the safety level of the infected person.

4. The method according to claim 1, characterized in that, The infection transmission probability is negatively correlated with the relative positions of the smart mobile terminal of the infected person and each smart mobile terminal, and the infection transmission probability is related to the protective measures of the infected person.

5. A source of infection location system, characterized in that, Including a server and at least one smart mobile terminal, used to implement each step in the method for locating the source of infection based on big data as described in any one of claims 1-4, wherein: The server is used to obtain and update the map library, wherein the map library stores the regional risk levels of each location at each moment; The server is used to obtain and update the personnel database, wherein the personnel safety levels of each person at each moment are stored in the personnel database; The intelligent mobile terminal is used to obtain the basic information of the person and the personnel safety level, and update the personnel safety level; The intelligent mobile terminal is used to display the map interface in real time, wherein the regional safety levels of each location are marked with set colors in the map interface; The intelligent mobile terminal is used to query the historical running track of the person and the information of the person's contact history; The intelligent mobile terminal is used to display the personnel safety levels obtained within the set distance of each intelligent mobile terminal.

6. A storage medium, characterized in that, The storage medium stores a computer program, which when executed by a processor, implements each step in the big data-based infection source location method according to any one of claims 1-4.

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